Job Title: Intern - Data Scientist (Medical Imaging and Computer Vision) Company: nference Job Category: Machine Learning Roles & Responsibilities: We work closely with leading medical institutions like the Mayo Clinic to extract insights from medical data—such as radiology images, patient notes, and lab results. Our team consists of top\-tier talent from institutions like MIT, Harvard, IITs, IISc , and more, combining expertise in computer science, biomedical research, and clinical medicine. About The Role We are looking for a motivated Data Science Intern to join our Medical Imaging and Computer Vision team. This internship offers a unique opportunity to gain hands\-on experience developing AI models that solve real\-world healthcare challenges. Key Responsibilities Assist in developing and evaluating deep learning models for medical imaging (e.g., classification, segmentation, object detection). Support image preprocessing, annotation, and data handling workflows involving DICOM and clinical image formats. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Machine Learning Engineer Company: Amgen Job Category: Machine Learning Roles & Responsibilities: India \- Hyderabad JOB ID: R\-251215 LOCATION: India \- Hyderabad WORK LOCATION TYPE: On Site DATE POSTED: Oct. 28, 2026 CATEGORY: Engineering ABOUT THE ROLE We are seeking a Machine Learning Engineer, Forecasting to join the Forecasting team within the AI \& Data organization. This role will build, deploy, and maintain machine learning systems that support forecasting and decision\-making across the organization. Key Responsibilities * Develop and maintain machine learning pipelines supporting forecasting and predictive analytics use cases. * Productionize statistical, machine learning, and Bayesian forecasting models developed by data scientists. * Build data ingestion, preprocessing, feature engineering, and model inference pipelines using structured and unstructured data. * Deploy ML models into production environments and support model lifecycle management. * Implement model monitoring, automated retraining, performance tracking, and alerting mechanisms. * Collaborate with data scientists to optimize model performance, scalability, and reliability. * Build reusable ML components, APIs, and services following software engineering best practices. * Contribute to CI/CD pipelines and MLOps workflows for automated testing and deployment. * Troubleshoot production issues, optimize system performance, and improve operational efficiency. * Document technical solutions and contribute to engineering best practices across the team. * Stay current with emerging machine learning engineering technologies and recommend improvements where appropriate. * 4\+ years of experience in Machine Learning Engineering, Software Engineering, Data Engineering, or a related field. * Experience building and deploying production machine learning applications. * Strong programming skills in Python and SQL. * Experience with machine learning libraries such as scikit\-learn, PyTorch, TensorFlow, or similar frameworks. * Experience building data pipelines and feature engineering workflows. * Familiarity with MLOps concepts including ML lifecycle management, CI/CD, model versioning, and monitoring. * Experience with cloud platforms such as Azure, AWS, or GCP. * Familiarity with containerization technologies such as Docker and orchestration platforms like Kubernetes. * Experience working with distributed data processing frameworks such as Spark or Databricks. * Understanding of software engineering best practices including testing, version control, code reviews, and documentation. * Strong analytical, problem\-solving, and communication skills. up. * Experience supporting forecasting or time\-series machine learning applications. * Familiarity with Bayesian or probabilistic forecasting models. * Experience deploying ML solutions in healthcare, biotech, retail, supply chain, or commercial analytics domains. * Experience with MLFlow, Airflow, Azure ML, Databricks, or similar ML platforms. * Familiarity with model explainability and monitoring tools such as SHAP, Evidently, or equivalent. * Exposure to modern AI technologies including Generative AI and LLM\-based applications is a plus. * Ability to work effectively in cross\-functional Agile teams. Work Location: Hyderābād, India Availability: Full time

Job Title: Technology Consultant - Senior Automation & AI Engineer Company: NTT DATA Job Category: Machine Learning Roles & Responsibilities: Role Summary We are seeking an experienced Senior Automation AI Engineer with strong expertise in Intelligent Automation, Artificial Intelligence, Generative AI, Process Automation, and Enterprise Solution Development. The ideal candidate will be responsible for designing, developing, and implementing automation and AI\-driven solutions that improve operational efficiency, productivity, and business outcomes. The candidate should possess hands\-on experience with Python, AI/ML frameworks, Generative AI platforms, workflow automation, APIs, cloud services, and integration technologies. The role will work closely with Business Stakeholders, Product Owners, Architects, Developers, Data Engineers, and Operations teams to identify automation opportunities and deliver scalable AI\-powered solutions. Day to Day Job Duties * Design, develop, and deploy AI\-powered automation solutions across business and technology functions. * Identify business processes suitable for automation and recommend appropriate AI and automation approaches. * Develop intelligent workflows using AI, Machine Learning, Generative AI, and automation platforms. * Build and integrate AI services utilizing Large Language Models (LLMs), NLP, and AI\-driven decision\-making capabilities. * Develop Python\-based automation frameworks, utilities, APIs, and reusable components. * Integrate enterprise systems using REST APIs, web services, databases, and middleware technologies. * Design and implement AI assistants, copilots, chatbots, and workflow automation solutions. * Work with structured and unstructured data for AI model training, inference, and process automation. * Collaborate with business teams to gather requirements and translate them into technical solutions. * Develop prompt engineering strategies and optimize AI model responses for business use cases. * Monitor AI solution performance, accuracy, reliability, and operational effectiveness. * Implement security, governance, compliance, and responsible AI best practices. * Conduct troubleshooting, root cause analysis, and performance optimization activities. * Support SIT, UAT, deployment, production rollout, and post\-production support activities. * Participate in Agile ceremonies including sprint planning, backlog grooming, design reviews, and retrospectives. * Mentor junior engineers and provide technical guidance on AI and automation best practices. * Programming: Python, SQL, JavaScript * Generative AI: OpenAI, Azure OpenAI, Claude, Gemini, LLM Integration * AI/ML: Machine Learning, NLP, Model Evaluation, AI Workflows * Prompt Engineering: Prompt Design, Optimization, AI Response Tuning * Automation Development: Workflow Automation, Business Process Automation, Intelligent Automation * Frameworks Libraries: LangChain, Semantic Kernel, Hugging Face, AI SDKs * Integration Technologies: REST APIs, Web Services, API Integrations * Data Technologies: SQL, Vector Databases, Data Processing, Data Validation * Cloud Platforms: Azure, AWS, GCP * DevOps CI/CD: Git, Azure DevOps, GitHub Actions, Jenkins * Security Governance: Responsible AI, Data Privacy, Access Controls * Methodologies: Agile, Scrum, SDLC * Experience with Microsoft Copilot, Copilot Studio, Power Platform, or Power Automate. * Experience building AI Agents, AI Assistants, and Autonomous Workflows. * Knowledge of Retrieval\-Augmented Generation (RAG) architectures. * Experience with Vector Databases such as Pinecone, Chroma, or Azure AI Search. * Experience with document intelligence, OCR, and intelligent document processing solutions. * Exposure to Data Engineering, Analytics, and Data Science projects. * Experience implementing AI governance and compliance frameworks. * Knowledge of MLOps, model deployment, and monitoring frameworks. * Experience working on enterprise digital transformation initiatives. * Strong stakeholder management and consulting skills. * 7–12\+ years of Software Engineering, Automation, or AI Engineering experience. * Strong expertise in Python, APIs, and enterprise automation development. * Hands\-on experience with Generative AI, LLMs, and AI\-powered solution development. * Experience designing and implementing intelligent automation frameworks. * Strong understanding of Prompt Engineering and AI integration patterns. * Experience working with cloud platforms and scalable enterprise architectures. * Experience collaborating with business and technical stakeholders. * Ability to drive AI and Automation initiatives from concept through production deployment. * Strong communication, leadership, and problem\-solving skills. * Passion for innovation, automation, and AI\-driven transformation. NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100\. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise\-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start\-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in RD. Work Location: Uttar Pradesh, India Availability: Full time

Job Title: Senior Principal Machine Learning Engineer Company: Eli Lilly and Company Job Category: Machine Learning Roles & Responsibilities: At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life\-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us. Role Overview We are looking for a Senior Principal Machine Learning Engineer to join the AI Engineering team, with a primary focus on Hands\-On Engineering (MLE) and MLOps \& Platform Reliability and GenAI \& Agentic Systems. This posting is at level R4 on our engineering ladder — see the level framing below for the expected scope of ownership and impact. Level framing: Recognized expert who mentors others; makes key technical decisions impacting multiple teams; leads resolution of highly complex challenges; cross\-functional influence; may engage with external partners as an authority. Core Responsibilities * Design and build production backend systems for agentic AI applications — API layers, backend\-for\-frontend (BFF) patterns, session/state management, and streaming for concurrent multi\-user workloads. * Lead resolution of highly complex, cross\-system technical challenges. * Set the technical bar for hands\-on engineering practice across the team. * Own GitOps and engineering\-governance standards across the team (version control, CI/CD, review, promotion). * Make key MLOps/platform decisions that affect multiple teams (e.g. deployment topology, observability strategy). * Drive triage and resolution of complex, cross\-system production incidents. * Own architecture for agentic AI systems, including routing, policy enforcement, and RAG/knowledge\-registry design. * Lead evaluation and adoption of new agent frameworks, LLMOps practices, and GenAI tooling across the team. * Implement authentication/authorization flows for agentic systems (OAuth/OIDC, on\-behalf\-of token exchange, secure credential storage). * Mentor other engineers on architecture, design patterns, and production engineering practices, and act as a role model for engineering rigor across the wider team. Key Tools \& Technologies * Cloud \& Data Infra: AWS (EC2/ECS, S3, Lambda, IAM, CloudWatch or equivalent); Databricks \& Unity Catalog * Foundational: Python; Git/GitHub; software engineering best practices; testing; SQL * MLOps \& Deployment: Docker, Kubernetes, Prefect; CI/CD (GitHub Actions); production monitoring; model versioning \& lineage; GitOps governance * GenAI \& Agentic Architecture: Claude or comparable LLMs; LangGraph or comparable agent frameworks; RAG architectures; vector databases (e.g. Pinecone); prompt engineering \& evaluation Work Location: Bengaluru East, Karnataka, India Availability: Full time

Job Title: Applied AI Engineer ServiceNow - Lead Software Engineer I Company: Deloitte Job Category: Machine Learning Roles & Responsibilities: Lead Applied AI Engineer I \- ServiceNow Role Overview: As a ServiceNow Lead Applied AI Engineer II, you will actively engage in your engineering craft, taking a hands\-on approach to building and enhancing high\-visibility, full\-stack products that serve the business and its users. Your expertise will be pivotal in delighting customers and users, while driving tangible value across Deloitte’s product and AI investments. You will leverage your extensive engineering craftsmanship and advanced proficiency across full\-stack software engineering and modern frameworks—together with applied AI fluency that lets you build GenAI and agentic capabilities directly into the products you deliver—consistently demonstrating your exemplary track record in delivering high\-quality, outcome\-focused solutions. The ideal candidate will be a role\-model leader and mentor, collaborating with cross\-functional teams to design, build, and ship products end to end, from concept through production. Key Responsibilities: \* Embrace and drive a culture of accountability for customer and business outcomes—and for the cost of achieving them. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high\-quality, lean designs and implementations, and owning the inference, token, and cloud cost of what you build. \* Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, low\-level architecture and component design, development, testing, integrations, and support. \* Maintain accountability for the integrity of architecture and technical stack to the enterprise standards and strategy. Manage dependencies, code design, implementation, quality, data, and ongoing maintenance and operations. Stay hands\-on, self\-driven, and continuously learn new approaches, languages, and frameworks. Create technical specifications, and write high\-quality, supportable, scalable code and review code of other engineers, mentoring them, to ensure all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams. \* Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time. \* Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning\-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions. \* Possess deep expertise in modern software engineering practices and principles, including AI and Agentic SSDLC to deliver daily product deployments using full automation from discovery to production to operations with all quality checks through SSDLC lifecycle. Be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate strong understanding of the full lifecycle product development, focusing on continuous improvement and learning. \* Quickly acquire domain\-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff. \* Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well\-structured arguments and trade\-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives. \* Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co\-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions. The team: US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost\-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom\-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting\-edge internal and go\-to\-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ways of thinking, ideas and perspectives, and bring more creativity and innovation to help solve our clients’ most complex challenges. This makes Deloitte one of the most rewarding places to work. Professional development At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state\-of\-the\-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India. Benefits to help you thrive Work Location: Karnataka, India Availability: Full time

Job Title: DATA SCIENTIST Company: TE Connectivity Job Category: Machine Learning Roles & Responsibilities: At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world. Job Overview We are looking for a Data Scientist who can solve business problems using Machine Learning, Statistical Modeling, and Generative AI. The role involves partnering with business stakeholders to identify opportunities, developing AI/ML solutions, building production\-grade models, and driving measurable business impact across areas such as manufacturing, supply chain, forecasting, quality, customer service, and enterprise productivity. Roles \& Responsibility AI \& Machine Learning * Design, develop, and deploy predictive and prescriptive analytics solutions. * Apply machine learning techniques including regression, classification, clustering, anomaly detection, forecasting, and optimization. * Conduct exploratory data analysis, feature engineering, and model evaluation. * Build scalable ML pipelines and monitor model performance. * Develop GenAI solutions using LLMs and foundation models. * Build RAG (Retrieval Augmented Generation) applications using vector databases and embeddings. * Utilize frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or similar agentic AI frameworks. * Evaluate and optimize prompts, retrieval strategies, and model performance. * Work with structured and unstructured data from enterprise systems. * Build data pipelines using SQL, Azure Data Factory, Databricks, or similar technologies. * Develop and deploy solutions on Azure, AWS, or cloud\-native platforms. * Collaborate with engineering teams to productionize AI solutions. * Translate business challenges into analytical frameworks and AI solutions. * Present insights and recommendations to stakeholders and leadership. * Drive adoption of AI solutions and measure business impact. About Te Connectivity TE Connectivity plc (NYSE: TEL) is a global industrial technology leader creating a safer, sustainable, productive, and connected future. As a trusted innovation partner, our broad range of connectivity and sensor solutions enable the distribution of power, signal and data to advance next\-generation transportation, energy networks, automated factories, data centers enabling artificial intelligence, and more. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Principal Machine Learning Engineer Company: Ema Job Category: Machine Learning Roles & Responsibilities: We are backed by industry leading investors including Accel, Naspers/Prosus, Creaegis, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production. We ship real systems that run real business processes at scale. Role Overview \& Key Responsibilities This is a high\-leverage leadership role that spans architecture, execution, and org\-building, and will shape the direction of our AI / ML initiatives at Ema. We are seeking an AI / ML technical leader who can take a vision and build it. As a Principal ML Engineer at Ema, you will be a senior technical leader responsible for shaping the machine learning roadmap, architecting large\-scale ML systems, driving innovation, and ensuring our mixture of expert models (LLM \+ SLM \+ Custom Model) is accurate and performant at scale. You will collaborate across teams (research, product, infra, data, etc.), mentor senior engineers, and influence strategy and execution at company\-wide levels. Responsibilities * Lead the technical direction of GenAI and agentic ML systems that power enterprise\-grade AI agents — spanning reasoning, retrieval, tool use, and integrations across various SaaS products. * Architect, design, and implement scalable production pipelines for model training, fine\-tuning, retrieval (RAG), agent orchestration, and evaluation — ensuring robustness, latency efficiency, and continuous learning. * Define and own the multi\-year ML roadmap for GenAI infrastructure — including agent frameworks, RAG systems, world\-class evaluation loops, and integration with MCP, browser, and vision pipelines. * Identify and integrate cutting\-edge ML methods / research (deep learning, large models, recommender systems, LLMs, etc.) into Ema’s products or infrastructure. * Research, prototype, and integrate cutting\-edge ML and LLM advancements (reasoning, memory architectures, multi\-modal perception, long\-context models, autonomous agents) into the platform. * Optimize trade\-offs between accuracy, latency, cost, interpretability, and real\-world reliability across the agent lifecycle — from prompt design to orchestration and execution. * Champion engineering excellence — drive observability, reproducibility, versioning, testing, and bias\-aware development across ML and agentic systems. * Mentor and elevate senior engineers and researchers, fostering a culture of scientific rigor, experimentation, and system\-level thinking. * Collaborate cross\-functionally with product, infra, and research teams to align ML innovation with enterprise needs — enabling secure integrations, privacy\-aware deployments, and scalable use cases. * Influence data strategy — guide how retrieval indices, embeddings, structured/unstructured corpora, and feedback loops evolve to improve grounding, factuality, and reasoning depth. * Drive system scalability and performance — ensuring ML agents and RAG pipelines can operate across billions of knowledge objects, diverse APIs, and real\-time enterprise contexts. Our culture \& Values * High Bar on Quality – We value excellence and expect world\-class execution. * Ownership \& Accountability – We take full responsibility for our work and outcomes. * Impact\-Driven Approach – We set ambitious goals and measure success through real\-world impact. * Team Collaboration \& Growth – We believe in continuous learning, knowledge sharing, and supporting each other. * No Hierarchy, Just Execution – Everyone is an individual contributor, focused on delivering results. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Site Reliablity Engineer Company: Trimble Inc. Job Category: Machine Learning Roles & Responsibilities: Accelerate Enterprise Intelligence as an AI/ML Engineer (P1\) Are you passionate about the foundational elements of machine learning and eager to contribute to innovative AI solutions within a collaborative, growth\-oriented team environment? Trimble is seeking an enthusiastic AI/ML Engineer (P1\) to join our Construction Management Solutions (CMS) team. This role offers an exceptional runway to accelerate your career in AI/ML engineering, working directly alongside seasoned data scientists and principal engineers to transform complex real\-world data into actionable, production\-grade enterprise tools. About Our Division: Construction Management Solutions (CMS) As an industry leader in construction software and ERP solutions, Trimble CMS empowers contractors worldwide. Our solutions seamlessly connect the office, team, and jobsite by integrating essential business functions like accounting, project management, and field operations. Operating on the Trimble Construction One (TC1\) connected ecosystem, our collaborative cloud platforms enhance transparency, efficiency, and profitability for organizations of all sizes across the globe. What Makes This Role Great This role provides a structured, high\-support environment designed to build deep competencies in applied machine learning, data engineering, and modern MLOps under direct mentorship. Working within our CMS engineering organization, you will gain hands\-on exposure to rich industrial datasets, participate across the full AI project lifecycle, and contribute to cutting\-edge model integration. Whether you are stepping in as an Associate Engineer (P1\) , you will enjoy real technical ownership, contributing to software tools that drive physical\-world operations globally. Key Exciting Responsibilities * Algorithm \& Model Development: Assist in developing, implementing, and fine\-tuning machine learning algorithms and foundational models, with direct exposure to advanced deep learning paradigms. * Data Engineering \& Preprocessing: Own data collection, sanitization, exploratory analysis, and feature engineering tasks to ensure data quality, consistency, and industry\-specific relevance. * Testing, Verification \& Code Health: Execute routine testing, debugging, and comprehensive documentation of ML codebases and pipelines to ensure reproducible, high\-performance systems. * ML Integration \& Operationalization: Support the integration of trained models into enterprise\-grade applications, adhering to standard architectural patterns while learning essential MLOps practices such as containerization, artifact tracking, and performance monitoring. * Cross\-Functional Collaboration: Partner with senior engineers and domain specialists to translate ambiguous business requirements into well\-defined machine learning tasks and actionable delivery milestones. Logistics * Job Level :P1 * Department: Construction Management Solutions (CMS) * Job Location: Chennai * Job Type: Full\-Time * You'll work on projects that truly matter: Our purpose\-driven culture means you'll be helping to build and deliver solutions that make work faster, safer, and more sustainable for millions of people worldwide. * Collaborate with like\-minded people: Our strong internal culture is a "hidden gem." You will work with a collaborative, supportive team that shares your purpose and fosters a genuine sense of belonging. * Be an owner: Trimble thrives on individuals who take initiative and embrace ownership. You'll find an entrepreneurial spirit where success is often "self\-authored," empowering proactive "doers." * Enjoy true flexibility: We offer flexible work arrangements, which are a significant driver for employees joining and staying with us. Work Location: Chennai, Tamil Nadu, India Availability: Full time

Job Title: Senior Manager Data Analytics Company: Optum Job Category: Machine Learning Roles & Responsibilities: The Senior Manager \- Data Analytics and AI Enablement will lead an enterprise analytics portfolio spanning business intelligence, reporting, advanced analytics, and insight delivery while helping the organization responsibly adopt AI/ML\-enabled capabilities. This role will translate complex business needs into scalable analytics solutions, lead multidisciplinary teams, modernize data and reporting practices, and partner with business, product, data science, engineering, architecture, and governance teams to deliver measurable outcomes. The position requires solid analytics leadership and practical exposure to predictive analytics, machine learning, Generative AI, natural language processing, and intelligent automation. It is designed for a leader who can identify high\-value use cases, define business and data requirements, guide evaluation and adoption, and partner effectively with technical specialists; it is not a hands\-on AI platform engineering role. Primary Responsibilities: * Analytics strategy and portfolio leadership: Define and execute a multi\-year analytics roadmap aligned with business priorities; manage dependencies, risks, and measurable value across reporting, BI, advanced analytics, and AI\-enabled initiatives * Insight delivery: Lead the development, enhancement, validation, and operation of dashboards, scorecards, self\-service analytics, predictive insights, and decision\-support solutions that are accurate, timely, scalable, and actionable * Business partnership: Work with senior business, product, operations, technology, and data leaders to translate strategic questions into prioritized analytics use cases, clear measures of success, and sustainable operating solutions * People leadership: Lead, coach, and develop managers, analytics leads, data analysts, BI professionals, and business analysts; manage capacity, performance, succession, skills development, and delivery commitments * Analytics modernization: Advance modern BI, cloud data, reusable metric, semantic model, automation, and self\-service practices; reduce fragmented reporting and manual effort in partnership with data engineering and architecture teams * Applied AI/ML enablement: Identify opportunities where predictive analytics, machine learning, Generative AI, NLP, or intelligent automation can improve decisions, experiences, productivity, or operational outcomes * AI/ML use\-case definition: Convert business challenges into well\-defined AI/ML use cases with expected value, data needs, evaluation criteria, human oversight, implementation dependencies, and adoption plans * Cross\-functional delivery: Partner with data scientists, AI/ML engineers, architects, product managers, data engineers, and governance teams to develop, validate, operationalize, and monitor AI\-enabled analytics solutions * Evaluation and responsible adoption: Establish business acceptance criteria and support evaluation of analytical and AI outputs for accuracy, relevance, consistency, explainability, traceability, fairness, and operational usefulness * Governance and controls: Establish standards for data quality, metric definitions, lineage, access, privacy, security, regulatory compliance, responsible AI, and analytics lifecycle management * Operational excellence: Monitor service levels, delivery performance, solution adoption, model or insight effectiveness, incidents, risks, and realized business benefits; drive continuous improvement and timely issue resolution * Executive communication: Present complex analytical findings, options, risks, and recommendations in clear, decision\-oriented language for senior stakeholders * Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements * Master's degree in Data Science, Analytics, Computer Science, Statistics, Business Analytics, or a related field * Experience delivering analytics or AI\-enabled solutions in healthcare, pharmacy, operations, financial services, or another regulated industry * Experience creating validation datasets, test scenarios, answer keys, evaluation criteria, or business acceptance frameworks for analytics or AI solutions * Experience leading analytics modernization, self\-service analytics, or BI\-to\-AI transformation initiatives * Experience measuring adoption, productivity improvement, operational impact, financial value, or other benefits from analytics investments * Experience with Agile delivery and work management platforms such as Azure DevOps or JIRA * Working familiarity with Python or R for analytics, prototyping, or model evaluation * Understanding of machine learning concepts, feature development, model evaluation, predictive analytics, and model monitoring * Exposure to Generative AI, large language models, Retrieval\-Augmented Generation, agentic workflows, NLP, or intelligent automation * Familiarity with MLOps, AI governance, responsible AI, human\-in\-the\-loop controls, and AI risk management Work Location: Hyderābād, India Availability: Full time

Job Title: Forward Deployed Engineer Company: Cindrel Job Category: Machine Learning Roles & Responsibilities: We are looking for a motivated Forward Deployed Engineer to work closely with clients, understand their business challenges, and develop practical technology solutions using AI, automation, and software engineering. Key Responsibilities * Work directly with clients to understand business requirements and technical challenges. * Develop and deploy AI\-powered applications and automation solutions. * Build and integrate APIs, databases, and third\-party tools. * Use Python and modern development frameworks to build practical solutions. * Identify opportunities to automate manual workflows and improve operational efficiency. * Troubleshoot technical issues and provide effective solutions. * Collaborate with internal teams to deliver projects within timelines. * Test, monitor, and continuously improve deployed solutions. * Communicate technical concepts clearly to clients and stakeholders. * Basic to intermediate knowledge of Python or another programming language. * Understanding of APIs, databases, and software development fundamentals. * Interest in Artificial Intelligence, Machine Learning, and automation. * Strong analytical thinking and problem\-solving skills. * Good communication and collaboration skills. * Willingness to learn new technologies and work on real\-world client projects. * Experience with AI tools, LLMs, or AI application development. * Familiarity with REST APIs, SQL, Git, and cloud platforms. * Knowledge of workflow automation tools or AI agents. * Experience in customer\-facing technical roles or project implementation. Work Location: Hybrid remote in Chennai, Tamil Nadu Work Location: Tamil Nadu, India Availability: Full time