Job Title: Data Scientist Company: Philips Job Category: Machine Learning Roles & Responsibilities: We're seeking with strong expertise in Agentic AI, Generative AI , Machine Learning, Predictive modelling, time\-series analysis, longitudinal pattern mining to join our team. In this role, you will design and build innovative and ethically responsible AI solutions that effectively address real\-world problems, balancing technical feasibility with user needs and business impact. Your role: * Design, train, and evaluate LLM\-based solutions for various use cases, including retrieval\-augmented generation (RAG), information retrieval \& search, chatbots, * structured information extraction and named entity recognition, text generation, summarization, and more * Design, develop, and deploy a Machine Learning, Predictive modelling. * Design, develop, and deploy agentic AI systems and autonomous AI workflows using large language models and advanced reasoning architectures * Perform the time\-series analysis, longitudinal pattern mining on the data sets. * Perform the Research \& Analysis (Example literature survey) * Clean, preprocess, and curate data for evaluation, fine\-tuning, and training * Work closely with stakeholders across the organization to understand business needs, formulate problems, and deliver data\-driven insights Keep up the latest advancements in generative AI research and integrate new techniques into the development process * * Data Analysis \& Interpretation * Prompt Engineering * Agentic AI * Generative AI * Predictive modelling * Time\-series analysis * Longitudinal pattern mining. * Data Governance * Statistical Methods * Statistical Programming Software * Business Intelligence Tools * Data Mining * Machine Learning Engineering Fundamentals * Machine Learning \& Deep Learning * Model Development \& Deployment * Research \& Analysis * Requirements Analysis * Root Cause Analysis (RCA) * Data Quality Management Systems Regulatory Compliance * Onsite roles require full\-time presence in the company’s facilities. Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations. This role is an office\-based role. Work Location: Karnataka, India Availability: Full time

Job Title: Software Engineer — Data Platform Company: Machinify India Job Category: Machine Learning Roles & Responsibilities: We're now opening a new hub in Bengaluru that isn't a satellite office or a support function: it's a genuine extension of one global Machinify, where local leaders run real teams and own real product and outcomes. The problems our teams solve are hard by design, which is exactly why they haven't been solved before, and why the work is worth doing. Joining now means building Machinify's India presence\- its people, culture, and way of working\- from the ground up, with real influence over what gets built and how. About the Role ------------------ This role sits within Data Platform Development, part of Machinify's Data Architecture, Tooling \& Frameworks organization. The Data Platform Development team builds the internal systems that power and extend the Machinify platform. We focus on scalable, reliable infrastructure for data processing, communication, and analytics across our products and customer\-facing systems. We work closely with the core Machinify platform (written in Scala) as its internal customers: we design and build orchestration and supporting services in Golang and Python that sit on top of the core engine. Our team builds internal products and analytics capabilities that improve performance, reliability, and extensibility, so the platform can scale with our customers and AI\-driven use cases. You'll design and build high\-performance backend systems that power these AI\-driven solutions, working with engineers, data experts, and innovators across the US and India. * Design and build scalable, high\-performance data software in Golang and Python. * Build and deploy Kubernetes\-based systems that manage containerized applications in cloud\-native environments. * Work with cross\-functional teams to understand customer and internal needs, so our systems keep up with future requirements. * Optimize the performance, reliability, and security of our backend infrastructure. * Work on data modeling and transformation that support machine learning workflows and AI\-powered applications. * Build agentic AI tooling and services that automate data engineering work (e.g., agentic ETL). * 3\+ years of hands\-on backend software development. * Strong Golang and/or Python. * Hands\-on experience with agentic AI (building with LLMs or agents, not only using chat tools). Strong experience is expected for the Senior level. * Strong understanding of ETL processes, data pipelines, and working with large datasets. * Kubernetes orchestration, containerization (Docker, Helm), and cloud\-native development. * Experience building scalable systems that handle high volumes of data and transactions. * A cloud platform (AWS, Azure, or GCP) and its ecosystem tools. * CI/CD pipelines and automated testing. * Strong problem\-solving skills and a passion for clean, maintainable code. Work Location: Karnataka, India Availability: Full time

Job Title: Senior AI/ML Software Engineer Company: AMD Job Category: Machine Learning Roles & Responsibilities: Whether you’re designing next\-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career. Responsibilities: Senior AI/ML Software Engineer THE ROLE: AMD is looking for a skilled and motivated software engineer to join the Machine Learning and Frameworks Org. As part of this team, you’ll build and maintain tools and infrastructure that automate functional and performance validation of deep learning libraries \& models across ROCm and GPU platforms. Your contributions will directly impact developer confidence, model portability, and transparent benchmarking for internal teams and the open\-source community. You will be a member of a core team of incredibly talented industry specialists and will work with the very latest hardware and software technology THE PERSON: We are seeking a software developer with strong technical expertise in Python and Linux\-based systems, who is passionate about quality assurance, benchmarking, and automation in the AI/ML space. The ideal candidate thrives in both collaborative and independent environments, demonstrates excellent problem\-solving skills, and takes ownership in defining goals and delivering impactful solutions. Experience working with machine learning frameworks, performance dashboards, or automation platforms is a strong plus. KEY RESPONSIBILITIES* Software Engineering Excellence: Proficiency in Python with experience in performance tuning, debugging, and robust test design, ensuring reliable, maintainable, high\-performance codebases. * CI/CD Pipeline Development: Design, implement, and manage efficient continuous integration and delivery pipelines using GitHub Actions and Buildkite to enable rapid and reliable software deployment. * Quality Assurance Enablement: Integrate automated testing frameworks into CI pipelines to ensure code quality, stability, and performance across development cycles. * Model Testing \& Validation: Automate functional and performance testing of AI libraries \& models across ROCm\-supported hardware (AMD and NVIDIA) using scalable tools and pipelines. * Benchmarking Infrastructure: Develop tools for continuous benchmarking and regression tracking across hardware generations and ROCm releases. * Dashboard \& Metrics Development: Build and maintain real\-time dashboards that report relevant performance, accuracy, and reliability metrics for both internal and public users. * Ecosystem Integration: Collaborate with teams like DeepLearningModels (DLM) and MADengine to support a wide range of models, including public and private/NDA workloads. * Client Enablement: Ensure out\-of\-box confidence for ROCm clients by validating model performance and functionality in standardized and reproducible environments. * Scalable Tooling: Contribute to the design of portable, easy\-to\-use Python interfaces that support multi\-node profiling, distributed workloads, and containerized deployments. * Open\-Source Contributions: Support public\-facing AMD GitHub repositories and Docker releases, enabling the community to run and validate models on ROCm. Work Location: Karnataka, India Availability: Full time

Job Title: Principal AI/ML Engineer Company: Mobileum Job Category: Machine Learning Roles & Responsibilities: Mobileum is a leading provider of Telecom analytics solutions for roaming, core network, security, risk management, domestic and international connectivity testing, and customer intelligence. More than 1,000 customers rely on its Active Intelligence platform, which provides advanced analytics solutions, allowing customers to connect deep network and operational intelligence with real\-time actions that increase revenue, improve customer experience, and reduce costs. Reporting to: Manager \- AI/ML Engineering Type: Individual contributor (technical lead) About the Role The AI/ML Development team executes Business Unit product roadmaps, delivering traditional machine learning solutions and implementing agentic AI capabilities where the business and products need them. We are a technology vendor serving the Telecom industry, and we are looking for a Principal AI/ML Engineer to be a senior technical owner of the ML solutions behind our products. The role is a hybrid that combines data science (developing and validating models) and ML engineering (building the training and inference pipelines and services that run them in production). Roles \& Responsibility: Data science and model development * Design and evolve end\-to\-end training and inference pipelines for the core product ML solutions, from data processing through deployment. * Build production inference pipelines in PySpark and inference services with REST endpoints, and tune Spark jobs to cut processing time and infrastructure cost at telecom data volumes. * Apply MLOps practices (monitoring, retraining, versioning, testing, deployment automation) that work across different customer environments. * Use AI and agentic AI to improve development and operational processes (AI\-assisted coding and review, testing, documentation, monitoring, data quality checks). * Enhance traditional ML solutions with agentic capabilities where they add value, using shared platform components from the AI Innovation \& Platforms team. Technical leadership * Set technical standards for code and model review, testing, and reusable components, including guardrails for AI\-assisted workflows. * Mentor junior engineers and data scientists, and technically lead selected projects. * Work with product, engineering, BU stakeholders, and telecom domain experts to keep delivery aligned with roadmap commitments. * Technical Leadership \& Mentoring * Problem Framing \& Ownership * Analytical \& Critical Thinking * Communication of Technical Trade\-offs * Cross\-functional Collaboration * Pragmatic Decision\-Making under Constraints * Learning Agility \& Innovation Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Senior Applied Scientist, Alexa Sensitive Content Intelligence (ASCI) Company: Amazon Job Category: Machine Learning Roles & Responsibilities: Build AI safety systems that protect millions of Alexa customers every day. As conversational AI evolves, you'll solve challenging problems in Responsible AI by ensuring LLMs provide safe, trustworthy responses, building AI systems that understand nuanced human values across cultures, and maintaining customer trust at scale. This is frontier research with immediate real\-world impact. You'll tackle problems that require innovative solutions: training models that remain truthful and grounded across diverse contexts, building reward models that capture the nuanced spectrum of human values across cultures and languages, and creating automated systems that continuously discover and address potential issues before customers encounter them. You'll collaborate with world\-class scientists, product managers, and engineers to transform state\-of\-the\-art ideas into production systems serving millions. * Deep expertise in state\-of\-the\-art NLP, Large Language Models * Track record of building scalable ML systems * Passion for impactful research—where frontier science meets real\-world responsibility at scale * Excitement about solving problems that will shape the future of AI Key job responsibilities The Responsible AI (RAI) team is at the forefront of building AI systems that are safe, ethical, and trustworthy. As a Senior Applied Scientist, you'll lead the scientific vision for end\-to\-end Responsible AI solutions—pioneering algorithms that eliminate false information, designing frameworks that hunt down vulnerabilities before bad actors find them, and developing models that understand human values across every culture we serve. Working alongside world\-class engineers and scientists, you'll push the boundaries of model training, building agentic AI systems that coordinate multiple autonomous agents to solve complex safety challenges—transforming bold research into production systems that protect millions of customers daily while withstanding attacks and delivering exceptional experiences. But here's what makes this role truly special: you'll shape the future. You'll lead efforts to identify, define, and mitigate risks early—protecting customers before they're impacted—and mentor the next generation of AI safety experts. You'll design multi\-agent architectures where distributed AI systems exhibit emergent collective intelligence while maintaining human oversight and control. Every innovation you drive—from consensus\-driven reasoning frameworks to sophisticated orchestration patterns—will set new standards for trustworthy AI at the world's largest scale. As a Responsible AI Scientist, you're at the frontier of AI safety—experimenting with breakthrough techniques that push the boundaries of what's possible. You partner with engineering to transform research into production\-ready solutions, tackling complex optimization challenges. You brainstorm with Product teams, translating ambitious visions into concrete objectives that drive real impact. Your expertise shapes critical deployment decisions as you review impactful work and guide go/no\-go calls. You mentor the next generation of AI safety leaders, watching ideas spark and capabilities grow. This is where science meets impact—building AI that's not just intelligent, but trustworthy and aligned with human values. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Data Scientist - Computer Vision Company: Philips Job Category: Machine Learning Roles & Responsibilities: Key Responsibilities AI/ML solution development * Analyse complex and high\-dimensional datasets and formulate hypotheses and proof\-of\-concepts. * Design, develop and evaluate Machine Learning and Deep Learning models . * Build solutions using Computer Vision, NLP, Generative AI and LLM\-based techniques , depending on the use case. * Evaluate state\-of\-the\-art AI/ML approaches and apply appropriate techniques to complex business problems. · Develop AI\-based Computer Vision applications for image\-related use cases. * Apply modern deep\-learning architectures and frameworks, including approaches such as YOLO and U\-Net , where appropriate. * Work with image\-processing and feature\-extraction techniques and develop robust model\-training and evaluation pipelines. · Develop solutions using LLMs, Transformers, RAG architectures and agentic frameworks . * Work closely with engineering teams to integrate AI models into production applications and enterprise workflows. * Monitor and continuously improve deployed model performance. * Contribute to robust and scalable data pipelines supporting advanced analytics and ML solutions. this role is an office role. Work Location: Karnataka, India Availability: Full time

Job Title: Senior, Platform Engineer Company: GSK Job Category: Machine Learning Roles & Responsibilities: About the Role: GSK's Enterprise AI team builds and deploys AI solutions at scale. Behind every AI product shipped is a shared platform: the Accelerator platform estate, GitHub Copilot, Claude Code/Cowork, Databricks AI Assistant, and Google Cloud data and AI services (BigQuery, Vertex AI, and GKE or Cloud Run). The Senior Platform Engineer (G6\) runs this estate, applying Site Reliability Engineering principles, managing strategic vendor relationships, and building the automation and infrastructure\-as\-code foundations that make the delivery roles faster and safer. This senior people\-manager role leads the platform engineering team and sets its technical direction. Most platform work is AI\-augmented: AI coding assistants handle the bulk of routine engineering, freeing the manager and team to focus on architecture, Google Cloud platform strategy, vendor strategy, and reliability. The role's direct customers are the Enterprise AI delivery engineers and the broader population of engineers and data scientists across GSK who build on the platform. Why This Role Exists: Platform availability and developer experience determine how fast Enterprise AI can build and deliver AI solutions. Platform outages or poor developer experience compound across every delivery team in the portfolio. The Senior Platform Engineer (G6\) is accountable for making sure this does not happen, for building the platform leverage that multiplies the productivity of every engineer, and for leading and growing the team that operates the platform. * Runs the platform estate that the delivery roles depend on, with SRE discipline, Google Cloud and vendor management depth, and AI\-native engineering practice. * Builds platform leverage through automation, reusable components, and self\-service capability that reduce repeated engineering work across the portfolio. * Leads and grows the platform team by hiring, coaching, and developing engineers toward greater platform ownership, and by raising the team's capability over time. Key Responsibilities: * Run the Google Cloud and SaaS platforms that Enterprise AI uses to build AI solutions, including BigQuery, Vertex AI, GKE or Cloud Run, and the Accelerator platform. Ensure availability, security, and cost efficiency. * Own Google Cloud platform architecture: design and operate BigQuery and Vertex AI environments, including partitioning, reservations, and cost controls, plus Pub/Sub and Dataflow ingestion and Cloud Composer orchestration. * Apply SRE principles: service\-level objectives, observability (Cloud Monitoring, OpenTelemetry), capacity planning, and vendor incident escalation across the platform estate. * Use AI coding assistants as the default mode of work; build automations that handle routine platform tasks at scale, using Claude Code, Codex, GitHub Copilot, and Databricks AI Assistant. * Manage the platform estate through Infrastructure\-as\-Code (Terraform, GitOps, and CI/CD) so configurations are versioned, auditable, and reproducible across Google Cloud and other platforms. * Treat platform users as customers by delivering self\-service capabilities, clear documentation, and fast onboarding for FDEs, FSEs, and data scientists. * Embed security, data privacy, and AI governance controls so AI solutions inherit compliance rather than building it from scratch. Set the Google Cloud security baseline: IAM and least\-privilege access, Cloud KMS (CMEK), VPC Service Controls, Secret Manager, and Organization Policies. Vendor Management \& Standards: * Act as the technical counterpart to strategic SaaS and cloud vendors (Microsoft, Anthropic, Databricks, and Google) on roadmap, capacity, integration, and incident escalation. Lead the Google Cloud relationship for data and AI services. * Continuously evaluate emerging AI tooling: pilot what looks promising through fast sandbox proofs of concept, and make adoption or deferral decisions. * Build and maintain reusable platform components so delivery roles do not reinvent the wheel across engagements. Team Leadership \& Reporting: * Lead and develop the platform engineering team by hiring, setting objectives, running 1:1s and performance reviews, and developing junior engineers toward greater platform ownership. * Track and report AI tooling adoption against the organisation's adoption goals for Enterprise AI leadership, and manage platform budget and cloud cost (FinOps) across Google Cloud and SaaS spend. * Own team delivery and prioritisation: set the team's roadmap and prioritise platform work against delivery\-team needs, balancing reliability, security, and developer experience. * Overall 0-2 years of experience. * 0-2 years of experience running SaaS or cloud platforms in a production setting. * Strong proficiency in Python and SQL. * Hands\-on experience with Infrastructure\-as\-Code (Terraform), GitOps, and modern CI/CD. * Hands\-on production experience with Google Cloud data and AI services (BigQuery, Vertex AI, GKE or Cloud Run, Pub/Sub, and IAM). * Daily use of AI coding agents (Claude Code, Codex, GitHub Copilot, Databricks AI Assistant) as a primary development mode. * Experience operating production services with SLOs and on\-call practices. * Experience managing or leading engineers, including hiring, performance management, and development. GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The obtaining of prior written authorization is a condition precedent to any agreement (verbal or written) between the employment business/ agency and GSK. In the absence of such written authorization being obtained any actions undertaken by the employment business/agency shall be deemed to have been performed without the consent or contractual agreement of GSK. GSK shall therefore not be liable for any fees arising from such actions or any fees arising from any referrals by employment businesses/agencies in respect of the vacancies posted on this site. Work Location: Karnataka, India Availability: Full time

Job Title: Sr AI/ML Engineer, Applied AI Company: Thermo Fisher Scientific Job Category: Machine Learning Roles & Responsibilities: Work Schedule Standard (Mon\-Fri) About The Role At Thermo Fisher Scientific, you’ll do meaningful work that makes a positive global impact. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner, and safer. With industry\-leading R\&D investment, we empower our teams to solve complex scientific challenges—from environmental protection to advancing healthcare and cancer research. As a Senior AI/ML Engineer, Applied AI, you will provide hands\-on technical leadership across the design, development, evaluation, and production deployment of advanced AI/ML solutions. You will architect and build machine learning and deep learning models, Large Language Model (LLM) applications, Retrieval\-Augmented Generation (RAG) solutions, and agentic workflows that power internal and external customer\-facing applications. You will work across the AI/ML lifecycle – from ideation, research, and experimentation through data engineering, model development and optimization, evaluation, performance tuning and deployment. Partnering closely with data scientists, software engineers, product teams and scientific stakeholders, you will translate complex business and scientific needs into scalable, reliable, and impactful AI/ML capabilities. This is a deeply hands\-on individual contributor role with significant technical leadership responsibilities. You’ll also mentor engineers, influence platform strategy, and ensure AI\-driven systems are accurate through consistent evaluation frameworks, engineering standards and technical best practices. A successful candidate in this role is expected to collaborate effectively with the broader teams, and consistently deliver well\-architected, production\-grade AI and Generative AI features supporting a variety of use cases and scientific products, with measurable impact on scientific workflows, customer outcomes and innovation velocity. : Key Responsibilities * Lead activities across the AI/ML lifecycle – from ideation, research, data engineering, model development and optimization, evaluation, performance tuning and deployment, while continuously engaging customers to gather feedback and incorporate it into solution development. * Iteratively develop, deploy and scale AI/ML models and solutions across life sciences, genomics, material sciences, and healthcare. * Contribute to the development of AI/ML models and solutions, following established model and system architectures, software design standards, reusable patterns, and best practices for AI and Generative AI solutions. * Apply evaluation\-driven approaches to AI/ML development by implementing and running evaluation frameworks, analyzing model performance, and using results to improve the quality and reliability of AI/ML solutions. * Build and deploy LLM\-powered services using Azure OpenAI, Anthropic Claude, and OpenAI\-compatible APIs. * Architect and implement agentic AI and RAG workflows, including data ingestion, chunking, embeddings, vector search, retrieval, tool calling, memory, and prompt engineering. * Design, develop, and integrate Generative AI systems using LangChain and LangGraph for agentic workflows and orchestration. * Integrate AI/Generative AI capabilities into enterprise platforms, scientific applications and end\-to\-end workflows. * Mentor and guide engineers across the AI/ML lifecycle, including model development, evaluation, and implementation of AI solutions. * Actively participate in Communities of Practice, influencing engineering standards and AI/Generative AI adoption strategies across the organization. * Communicate effectively with technical and non\-technical stakeholders through clear documentation, architecture diagrams and design reviews. * Stay current with advancements in AI/ML, Generative AI, agentic frameworks, and LLM ecosystems, and apply relevant innovations to enhance internal tools, scientific solutions and customer\-facing products. Work Location: Bengaluru East, Karnataka, India Availability: Full time

Job Title: Junior Data Scientists Company: Siemens Healthineers Job Category: Machine Learning Roles & Responsibilities: Role Job Requirements To contribute to the end\-to\-end development and product lifecycle management of artificial intelligence and machine learning (AI/ML) systems as part of an R\&D organization. The Junior Data Scientist supports the definition of intended algorithm performance, the development and curation of representative data and annotations, the development of AI/ML algorithms, and the generation of scientific evidence demonstrating stand\-alone algorithm performance. The Candidate Is Expected To * Apply scientific, statistical, machine learning, and software engineering methods to develop and evaluate AI/ML algorithm components for defined product use cases. * Work with experienced Data Scientists, product management, clinical or domain experts, software developers, and quality and regulatory functions to translate customer needs and the intended use into measurable algorithm performance targets. * Support the definition, sourcing, curation, documentation, and maintenance of representative data cohorts and annotations required for training, tuning, and evaluation. * Plan and execute reproducible scientific evaluations that provide objective evidence of algorithm performance, limitations, and suitability for the intended use. * Contribute the Data Science work products and evidence required for integration of AI/ML algorithm components into products and for their verification, validation, regulatory release, and lifecycle monitoring. What are my responsibilities? As a Junior Data Scientist, You Are Required To * Support the finalization of product and algorithm concepts by translating customer needs, intended use, clinical or technical requirements, and applicable regulatory considerations into measurable state\-of\-the\-art performance targets. * Contribute to the definition of the AI/ML development and scientific evaluation strategy for assigned algorithm components under the guidance of experienced Data Scientists. * Perform exploratory data analysis and data risk assessments to identify data gaps, quality issues, potential bias, confounding factors, outliers, and limitations that may affect algorithm development or evaluation. * Define and document data needs for training, tuning, and evaluation, including relevant subgroups and acceptance criteria, so that data cohorts are representative of the intended use and aligned with the product and regulatory strategy. * Support the specification of annotations, acceptance criteria, and quality controls; collaborate with qualified internal or external suppliers on sourcing data and annotations. * Curate, version, maintain, and document representative data cohorts and ensure data provenance, traceability, quality, and fitness for purpose together with data management stakeholders. * Design, implement, train, tune, and technically characterize AI/ML algorithm components using appropriate machine learning, deep learning, statistical, or generative AI methods. * Define scientifically justified metrics, evaluation methods, test cases, and acceptance criteria to assess stand\-alone algorithm performance, including relevant aspects such as accuracy, robustness, reliability, generalizability, explainability, bias, and subgroup performance. * Implement and execute reproducible bench tests on representative evaluation cohorts and relevant subgroups as part of the verification and validation strategy. * Analyze and interpret evaluation results, investigate failure modes, document residual limitations, and derive evidence\-based recommendations for algorithm improvement and product decisions. * Document development and evaluation activities and contribute to Data Science work products such as data management information, annotation specifications, scientific evaluation test cases, and scientific evaluation reports. * Provide scientific evidence and technical input for product reviews and regulatory submissions and support responses to questions concerning data, annotations, evaluation methods, and stand\-alone algorithm performance. * Support the design and execution of clinical investigations, reader studies, or other studies when additional evidence is required by the product or regulatory strategy. * Collaborate with software engineering and MLOps functions to establish reproducible pipelines, versioned artifacts, automated tests, controlled deployment, and integration of algorithm components into the product. * Help define and implement monitoring metrics for detecting data anomalies, outliers, and algorithm performance drift across the product lifecycle. * Regularly review advances in Data Science and AI and assess their applicability to the development and evaluation of AI/ML products. Desired Knowledge \& Experience * Sound understanding of machine learning, deep learning, statistical analysis, experimental design, and model evaluation. * Active programming skills in Python and practical experience with libraries and frameworks such as NumPy, Pandas, SciPy, scikit\-learn, PyTorch, TensorFlow, or Keras. * Hands\-on experience with the development workflow of AI/ML models, including data preparation, training, tuning, evaluation, error analysis, reproducibility, and documentation. * Ability to define meaningful performance metrics, evaluation cohorts, subgroup analyses, test methods, and acceptance criteria for the intended use of an AI/ML algorithm. * Understanding of data quality, representativeness, bias, annotation quality, data provenance, and traceability in AI/ML development. * Knowledge of Machine Learning Operations (MLOps) concepts and tooling, including source and data versioning, reproducible pipelines, experiment tracking, automated testing, CI/CD, deployment, and monitoring. * Hands\-on exposure to current Large Language Models and Generative AI, including foundation models, prompting, retrieval\-augmented generation, and model adaptation or fine\-tuning. * Knowledge of Agentic AI, including tool\-using models, multi\-step workflows, orchestration, memory, and autonomous or semi\-autonomous decision paths, is an advantage. * Experience or strong interest in the systematic evaluation of LLM, Generative AI, and Agentic AI systems, including task\-specific benchmarks, groundedness and factuality, robustness, reproducibility, human evaluation, safety and guardrail testing, tool\-use correctness, and analysis of failure modes. * Experience with databases and query languages such as SQL; knowledge of Kusto Query Language, Snowflake, or graph databases such as Neo4j is an advantage. * Exposure to cloud\-based data and AI environments, preferably Microsoft Azure, such as Azure Blob Storage, Azure Databricks, Azure Data Factory, Azure Machine Learning, Azure Monitor, or Azure DevOps. * Experience with structured and unstructured data, for example machine logs, event data, Parquet files, text data, or multimodal data. * Knowledge of healthcare, medical technology, clinical data, or interoperability standards such as DICOM is preferred. * Basic project management skills and familiarity with working in cross\-functional R\&D or product\-development teams. Required Soft Skills \& Other Capabilities * Scientific mindset, strong analytical ability, and attention to detail. * Commitment to objective evidence, reproducibility, traceability, data integrity, and responsible AI development. * Curiosity and resilience to investigate unexpected results, challenge assumptions, and improve models based on evidence. * Collaborative approach to working with Data Scientists, domain experts, software engineers, product management, and quality and regulatory stakeholders. * Ability to work independently within an agreed scope and to seek guidance when technical, scientific, product, or regulatory implications require alignment. * Clear written and verbal communication skills in English, including the ability to explain methods, results, uncertainties, limitations, and risks to technical and non\-technical stakeholders. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Senior Machine Learning Engineer Company: Siemens Job Category: Machine Learning Roles & Responsibilities: We believe that a business can truly thrive only when its people are growing. That’s why we always put our people first. Our global and diverse team is here to support you—and challenge you—to grow in new ways. Who knows where our shared journey will take you? * Be the Architect \& Builder: Act as the technical engine for AI products. You are responsible for designing, developing, and implementing end\-to\-end AI products that solve high\-impact industrial challenges. * Revolutionize the Build: You don't just follow standard ML workflows; you innovate on how to build them faster. You will champion the use of Agentic Coding Frameworks and LLMOps to accelerate our time\-to\-market and automate the development lifecycle. * Iterate at Speed: Lead the technical execution of the product lifecycle using a lean, MVP\-driven approach. You focus on rapid prototyping, turning user feedback into code, and ensuring continuous deployment of production\-grade models. * Bridge Code \& Value: You speak "Deep Learning" and "Business Value" fluently. You will translate complex AI/Cloud architectures into scalable technical solutions, ensuring our technical debt stays low while our value delivery stays high. * Technical Leadership \& Mentorship: In a large organization, technical clarity is key. You will proactively clear technical roadblocks, mentor junior engineers, and align stakeholders on the feasibility and scalability of AI solutions. This role is based in Bangalore, offering the opportunity to work with teams that impact entire cities, countries—and the shape of things to come. Work Location: Karnataka, India Availability: Full time