Job Title: AI/ML Engineer (Data Engineering + AI Focus) Company: A.P. Moller - Maersk Job Category: Machine Learning Roles & Responsibilities: A.P. Moller – Maersk is the global leader in container shipping services. The business operates in 130 countries and employs 80,000 staff. An integrated container logistics company, Maersk aims to connect and simplify its customers’ supply chains. Today, we have more than 180 nationalities represented in our workforce across 131 Countries and this mean, we have elevated level of responsibility to continue to build inclusive workforce that is truly representative of our customers and their customers and our vendor partners too. In this role as an AI/ML Engineer within the Global Data \& Analytics (GDA) team, you will build and scale data\-intensive AI/ML solutions that power intelligent decision\-making across Maersk’s supply chain ecosystem. This role combines strong data engineering foundations with applied AI/ML expertise, enabling the development of robust data pipelines, scalable ML systems, and production\-grade AI applications. Key Responsibilities: * Partner with business, product, and engineering teams to define scalable data and AI/ML solutions aligned with measurable business outcomes. * Design, build, and maintain robust data pipelines and data platforms using Python, Spark/PySpark, and cloud\-native services. * Develop and deploy end\-to\-end AI/ML solutions, including data ingestion, feature engineering, model training, evaluation, and production deployment. * Architect and optimize large\-scale data processing systems on cloud platforms (Azure/AWS), ensuring performance, reliability, and cost efficiency. * Implement and manage MLOps and DataOps practices, including CI/CD pipelines, model versioning, monitoring, and automated retraining. * Work with LLMs and Generative AI systems, integrating them into production workflows using frameworks such as LangChain, LlamaIndex, or similar. * Design and maintain data models (batch and streaming) that support analytics, reporting, and AI use cases. * Ensure data quality, governance, and observability across pipelines and ML systems. * Optimize infrastructure and workloads for cost, scalability, and performance, including efficient use of compute and storage. * Collaborate with engineering teams to deploy solutions using containerization and orchestration (Docker, Kubernetes). * Mentor junior engineers and contribute to engineering excellence through code reviews and best practices. * 7\+ years of experience across Data Engineering and AI/ML engineering in production environments. * Strong programming skills in Python and SQL, with hands\-on expertise in Spark/PySpark for large\-scale data processing. * Deep experience with cloud platforms (Azure or AWS), including services for data engineering, ML, and distributed systems (e.g., Databricks, Synapse, EMR, S3, ADF, etc.). * Hands\-on experience in building and deploying scalable data pipelines and ML systems. * Strong understanding of data modeling (data lakes, lakehouse, warehouse, medallion architecture). * Experience with MLOps frameworks (e.g., MLflow) and production model lifecycle management. * Practical experience with LLMs / Generative AI applications, including RAG, document processing, or workflow automation. * Experience with containerization (Docker) and orchestration (Kubernetes). * Strong understanding of system design, scalability, and cost optimization in cloud environments. * Experience with data quality, observability, and monitoring frameworks. * Ability to translate business problems into scalable technical solutions with measurable impact. * Prior experience in logistics, supply chain, or operations is a plus. * Experience in simulation, optimization, or operations research is an added advantage. We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com. CORE SKILLS Programming: Writing code to manipulate, analyze, and visualize data, often using languages like Python, R, and SQL. Proficiency Level: Proficient AI \& Machine Learning: Creating systems that can perform tasks that typically require human intelligence. Using Machine learning (ML), a subset of AI that uses algorithms to learn from and make predictions based on data Proficiency Level: Proficient Data Analysis: Inspecting, cleansing, transforming, and modeling data to discover useful information, draw conclusions, and support decision\-making Proficiency Level: Foundational Machine Learning Pipelines: Using automated workflows that manage the end\-to\-end process of training and deploying machine learning models. Proficiency Level: Proficient Model Deployment: Making a trained machine learning model available for use in production environments. Proficiency Level: Proficient SPECIALIZED SKILLS Big Data Technologies: Using continuous integration and continuous delivery (CI/CD) pipelines to automate the process of software development, including building, testing, and deploying code Natural Language Processing (NLP): Focusing on the interaction between computers and humans through natural language. Data Architecture: Designing and structuring of data systems, ensuring that data is stored, managed, and utilized efficiently Data Processing Frameworks: Using tools and libraries to process large data sets efficiently, such as Apache Hadoop and Apache Spark. Technical Documentation: Creating and maintaining documentation that explains the functionality, use, and maintenance of software or systems. Deep Learning: Using a subset of machine learning involving neural networks with many layers, used to model complex patterns in data. Statistical Analysis: Collecting and analyzing data to identify patterns and trends, and to make informed decisions. Data Engineering: Designing and building systems for collecting, storing, and analyzing data at scale. Definition of Proficiency Levels: Foundational: This is the entry level of the skill, typically expected when starting a new role or working with the skill for the first time. You rely on strong manager support, coaching, and training as you build the capability to progress to higher proficiency levels. Proficient: This is the level at which you are considered effective in the skill. You demonstrate more than just functional competence—you begin to have a noticeable impact in your role by applying the skill consistently and meaningfully. You require only minimal support, coaching, or training to apply the skill successfully. Advanced: This is the level where you move beyond meeting expectations to actively leading, influencing, and delivering considerable impact across the wider business. You are seen as a role model, demonstrate the skill independently, and require little to no manager support. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Data and Applied Scientist -(AIREE) ARC - AI Research to Capability Company: SAP Job Category: Machine Learning Roles & Responsibilities: The Role * Design, build, and deploy scalable machine learning services and APIs on SAP Business * Technology Platform (BTP) and other cloud platforms. * Productionize experiments and PoCs — taking research prototypes from the ARC team to * production\-ready state with high availability, performance, and reliability. * Build and maintain reusable AI engineering foundations: agent harnesses, SDKs, MCP * servers and tools, and common components that other teams can adopt. * Operationalize evaluation tooling and observability at scale, so teams know whether their AI * is ready before release and stays healthy after it ships. * Develop and maintain CI/CD pipelines, infrastructure\-as\-code, and MLOps workflows to * streamline model deployment, versioning, and monitoring. * Collaborate with data and applied scientists to productionize models, optimize inference * performance, and integrate capabilities seamlessly into enterprise applications. * Build robust, secure, and compliant cloud\-native applications, leveraging containerization * (Docker, Kubernetes) and serverless architectures. * Contribute to architectural decisions for ML and AI platforms, balancing scalability, cost,and developer experience. * Stay current with advances in MLOps, cloud engineering, Generative AI, and agentic * systems — and bring what works back into the team's foundations. Bring out your best SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end\-to\-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose\-driven and future\-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best. For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training. Requisition ID: 451384 \| Work Area: Software\-Design and Development \| Expected Travel: 0 \- 10% \| Career Status: Professional \| Employment Type: Regular Full Time \| Additional Locations: Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Solution Architect - Gen AI Company: Empower Job Category: Machine Learning Roles & Responsibilities: The Solution Architect provides technical leadership and designs complex solution architectures that support business strategy and streamline technology\-enabled workflows. This role partners closely with business owners, product, data, and engineering teams to document current\-state systems and design scalable, resilient, and secure cloud\-based solutions. This position focuses on emerging technologies, including AI, Generative AI, and machine learning, and guides solutions from research and analysis through architecture, delivery support, and operational readiness. What you will do: * Lead discovery with business and technology partners to understand objectives, constraints, current\-state systems, and integration points. * Document current\-state architecture and define target\-state designs including system context diagrams, component designs, integration patterns, and data flows. * Design and modernize applications into cloud\-compatible or cloud\-native architectures using microservices, serverless, and event\-driven patterns where appropriate. * Create strategies, roadmaps, and migration designs for transitioning applications and data workloads to cloud platforms. * Design AI and ML\-enabled solutions, including model integration into products and business processes, and patterns for scalable inference and low\-latency serving where needed. * Design Generative AI solution patterns, such as retrieval\-augmented generation, tool and API integration, prompt and context management, and evaluation approaches. * Define reference architectures for AI platforms and enabling capabilities, such as data pipelines, feature and embedding generation, vector storage, model endpoints, and integration with enterprise APIs. * Define integration patterns for agent toolchains using standards and common approaches such as Model Context Protocol (MCP), skills and plugin manifest standards, function calling with JSON Schema tool definitions, OpenAPI\-based tool specifications, and event\-driven or message\-based tool execution patterns. Ensure integrations address authentication and authorization, data minimization, auditability, and isolation boundaries. * Incorporate security\-by\-design practices into architectures, including identity and access controls, encryption, secrets management, secure networking, and audit logging. * Partner with governance and risk stakeholders to ensure responsible AI considerations are incorporated, including privacy, explainability, safety, compliance, and model risk controls as applicable. * Drive alignment and adoption of proposed solutions by clearly communicating tradeoffs, risks, and value and obtaining stakeholder alignment and governance approvals. Selling means internal alignment and decision support, not external pre\-sales. * Support teams responsible for testing and validation and help triage and resolve design\-related issues found during development, UAT, or production. * Perform other duties as assigned * Hands\-on experience with GenAI and LLM solutions, including retrieval\-augmented generation, embeddings, evaluation, and production monitoring. * Experience with AI and ML platforms or services, such as AWS SageMaker, Amazon Bedrock, Azure AI, Azure OpenAI, or Google Vertex AI. * Familiarity with MCP\-based integrations and related agent tool standards, including skills and plugin manifests, function calling schemas, and OpenAPI\-defined tools, plus secure enterprise integration patterns. * Container and orchestration experience, such as Docker and Kubernetes, and cloud container platforms like ECS or EKS. * Experience with vector databases and search technologies and associated indexing and retrieval patterns. * Experience with enterprise observability, including centralized logging, tracing, metrics, alerting, and operational readiness. * Database and procedural development experience, including PL/SQL, and strong data modeling concepts. * Familiarity with responsible AI practices, governance controls, and security considerations specific to AI systems. Work Location: Karnataka, India Availability: Full time

Job Title: Senior Data Scientist Company: LSEG Job Category: Machine Learning Roles & Responsibilities: The Emerging Tech Standard Delivery Team drives the adoption of advanced technologies and develops enterprise‑ready solutions for D\&A Operations. In this role, the individual partners with Operations and Technology teams to design data‑driven solutions that deliver clear business and customer value. Role, Responsibilities \& Key Accountabilities: * Own the product vision for an industry‑leading data management framework, covering data acquisition, cleaning, transformation, and related workflows. * Support Lead Data Scientist on end\-to\-end AI/ML lifecycle: problem definition, design, experimentation, deployment, and continuous improvement. * Define an optimized user experience for financial analytics data pipelines, unifying multiple tools and services into an integrated workflow. * Partner with analytics domain experts to understand business data needs and translate them into a practical platform and framework strategy. * Lead the execution of this strategy in close collaboration with engineering and project delivery teams. * Communicate product goals, progress, and achievements to product, engineering, business leaders, sales, proposition, support, and other internal stakeholders. * Stay informed on financial analytics market trends to maintain a forward‑looking, future‑ready strategy. * Continuously learn and adapt to emerging technologies and techniques in financial analytics. * Develop and deploy production‑grade AI models and data‑driven solutions aligned with strategic objectives. * Tune and optimize AI models to improve accuracy, performance, and scalability. * Evaluate third‑party AI capabilities using both functional and non‑functional criteria. * Establish and enforce coding standards to ensure a maintainable, robust codebase. * Collaborate with Software Engineers and cross‑functional teams to define requirements, set direction, and shape development roadmaps. * Hands‑on experience in data science, including Natural Language Processing, Large Language Models, prompt engineering, and Retrieval‑Augmented Generation (RAG). * Skilled in training, testing, and validating deep learning models as well as classical machine learning models. * Ability to design and implement evaluation frameworks for automation solutions based on business requirements. * Experience building solutions and onboarding workloads on AWS or other cloud platforms. * Expertise in web crawling and scraping techniques, entity identification and extraction, and advanced pre‑ and post‑processing methods using emerging technologies such as prompt engineering. * Proficient in processing structured, semi‑structured, and unstructured data from PDFs and scanned documents. Required Skills: * 0-1 years of experience in data science, analytics, or statistical modelling roles. * Strong foundation in data analytics, feature engineering, NLP, predictive modelling, LLMs, and RAG workflows. * Expertise in Python and core ML/DL libraries (TensorFlow, PyTorch, Scikit‑learn), with demonstrated experience in developing and productionizing AI models. * Proven ability to apply strong statistical analysis skills, including probability and applied statistics, to model development and evaluation. * Experience with Git‑based version control and CI/CD pipelines (GitLab/GitHub runners). * Strong understanding of relational databases, large‑scale data processing, and statistical programming. * Familiarity with MLOps principles and experience deploying solutions on cloud platforms (AWS and/or Azure). * Hands‑on experience with commercial or open‑source data management tools. * Excellent communication and presentation skills, capable of simplifying complex technical concepts for both technical and business audiences. * Strong influencing and collaboration skills, supporting cross‑team execution and alignment. * Ability to diagnose and resolve complex technical and business problems using deep analytical and industry knowledge * Ability to set and uphold coding standards. * Hands\-on experience with leading commercial or open\-source data management tools. * Excellent written, verbal, and presentation skills, with the ability to present to peers, senior management, and cross\-functional partners. * Broad business awareness and understanding of relevant internal business relationships. LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth. If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Python and AI/ML Developer Company: Terralogic Job Category: Machine Learning Roles & Responsibilities: Role Overview Are you excited about the future of AI and how it can revolutionize network infrastructure? We are looking for an enthusiastic Python and AI/ML Developer to help us build the next generation of AI\-powered solutions for network operations, automation, monitoring, and troubleshooting. In this role, you’ll get the unique opportunity to blend backend development with practical networking concepts, machine learning, and cutting\-edge Generative AI. If you love solving complex puzzles and want to see your code make a real\-world impact, we want to meet you! Your Journey \& Responsibilities * Owning Your Work: Delivering high\-quality code on time, collaborating openly with your teammates, and growing through constructive feedback. * Building Scalable Systems: Designing and deploying reliable, secure, and high\-performance backend microservices and APIs using Python and FastAPI. * Innovating in AI \& Networking: Crafting AI/ML solutions for network health analysis, incident classification, and troubleshooting assistants. * Developing Smart Agents: Building AI agents that can handle network diagnostics and talk to each other seamlessly using MCP/A2A frameworks. * Automating Infrastructure: Writing smart Python workflows for device discovery, automated configuration checks, and pre/post\-change validation. * Handling Data Pipelines: Engineering pipelines that ingest, normalize, and analyze massive amounts of network logs, telemetry, and event data. * Ensuring Security \& Excellence: Implementing smart access controls and audit logs for AI\-assisted actions, while constantly troubleshooting, optimizing performance, and maintaining automated tests. This is a rare opportunity for a developer early in their career to work directly with highly advanced GenAI Agentic workflows and network automation frameworks . You won't just be a cog in a machine—with a cohort of 10 people starting together, you will have a direct support system, mentorship, and a platform to fast\-track your technical skills. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Applied Scientist Company: Amazon Science Job Category: Machine Learning Roles & Responsibilities: Description Help millions of authors around the world get their books published, discovered, and supported. As one of the first scientists on our new team in Bengaluru, you'll help turn ideas into models authors rely on every day, building agentic solutions with large language models (LLMs), multimodal models, and fine\-tuning. Key job responsibilities * Build the multi\-agent system behind KDP's author support assistant: orchestration across specialized agents and tools, personalization, and the evaluation that drives its continuous improvement. * Build multimodal models of book attributes, and use them for similar\-book search across languages, catalog quality, and category and keyword recommendations. * Post\-train open models on KDP expertise (for example with supervised fine\-tuning and reinforcement learning), and deploy them where they beat general\-purpose models on accuracy, cost, or speed. * Work closely with our scientists in the US and with engineering partners to take your work to production, design rigorous offline and online experiments, and write clear readouts with recommendations. About The Team Kindle Direct Publishing (KDP) lets anyone publish a book. We are the science organization for Amazon's Books business, now building our science teams in Bengaluru. Our team works in three connected areas: a support assistant that answers authors' questions from their own account data, in every language KDP supports; multimodal models that use book attributes to keep the catalog trustworthy and help authors reach the right readers; and fine\-tuned models that power the assistant and catalog models with KDP expertise. We serve authors, from first\-time writers to full\-time publishers. You will work closely with engineering, product, and policy partners. We value safety before speed and shared foundations over one\-off fixes. Scientists here get dedicated time for innovation, which can lead to patents and conference papers. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Associate Data Engineer (Data Intelligence) Company: Chalhoub Group Job Category: Machine Learning Roles & Responsibilities: What You'll Be Doing Support the AI/ML squad by preparing model training datasets, executing feature engineering tasks, and assisting with prompt design and API integration for the Group's generative AI and machine learning models. * Query, prepare, and clean model training datasets using SQL and Python (Pandas, NumPy) in Jupyter Notebooks. * Execute basic feature engineering tasks under the guidance of senior engineers. * Assist in prompt design and testing AI agents on the company's enterprise GenAI platform (Alia). * Support the build and testing of generative AI features using LLM APIs and AI tools. * Support API integration for machine learning models via REST APIs. * Run model training and evaluation experiments, recording metrics and results. * Assist with model monitoring, flagging performance or data quality issues to senior engineers. * Document datasets, experiments, and observations to support reproducibility. * Collaborate with AI/ML engineers, learning and applying engineering best practices. What We Can Offer You With us, you will turn your aspirations into reality. We will help shape your journey through enriching experiences, learning and development opportunities and exposure to different assignments within your role or through internal mobility. Our Group offers diverse career paths for those who are extraordinary, every day. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Senior Engineer AI Company: Litmus7 Job Category: Machine Learning Roles & Responsibilities: * 0-1 years of experience in machine learning engineering and AI development. * Deep expertise in machine learning algorithms and techniques like supervised/unsupervised learning, deep learning, reinforcement learning, etc. * Solid experience in natural language processing (NLP) \- language models, text generation, sentiment analysis, etc. * Proven understanding of generative AI concepts like text/image/audio synthesis, diffusion models, transformers, etc. * Expertise in Agentic AI and building real world applications using the same. * Experience working with Agentic AI frameworks like Langgraph , ADK, Autogen etc. * Hands\-on experience in developing and deploying generative AI applications (text generation, conversational AI, image synthesis, etc.) * Experience in MLOps and ML model deployment pipelines. * Proficiency in programming languages like Python, and ML frameworks like TensorFlow, PyTorch, etc. * Knowledge of cloud platforms (AWS, GCP, Azure) and tools for scalable ML solution deployment. * Experience with data processing, feature engineering, and model training on large datasets. * Familiarity with responsible AI practices, AI ethics, model governance and risk mitigation. * Understanding of software engineering best practices and applying them to ML systems. * Design, develop and optimize machine learning models for applications across different domains. * Build natural language processing pipelines for tasks like text generation, summarization, translation, etc * Develop and deploy cutting\-edge generative AI \& Agentic AI applications. * Implement MLOps practices \- model training, evaluation, deployment, monitoring, and maintenance. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Sr Engineer - AI COE Company: Tata Communications Job Category: Machine Learning Roles & Responsibilities: Role Summary We are hiring a Sr. Engineer (2\+ years) for the AI CoE to build and deploy Generative AI, RAG, Agentic AI, and Machine Learning solutions. This role combines LLM\-driven applications with strong ML fundamentals, supporting scalable and monetizable AI products for telecom and enterprise use cases. Key Responsibilities * Build and deploy LLM\-based applications, RAG, and Agentic RAG systems * Develop multi\-agent workflows using tools like LangChain, LlamaIndex, LangGraph, Azure, and AWS Bedrock * Integrate MCP tools, APIs, and function\-calling into AI systems * Design prompting strategies, embeddings, and vector search pipelines using Milvus / FAISS / Pinecone * Implement structured output generation for LLM responses (JSON/schema\-driven outputs) * Apply machine learning techniques (classification, clustering, predictive modeling) for telecom and enterprise use cases * Perform data preprocessing, feature engineering, and model evaluation * Optimize solutions for performance, scalability, cost, and latency * Develop backend APIs using FastAPI for serving AI/ML models * Containerize applications using Docker for scalable deployment * Implement monitoring, logging, and observability using Grafana and ELK stack * Enable LLM traceability and observability using Langfuse etc. * Collaborate with product and engineering teams to deliver production\-grade AI solutions Additional Note Role involves hands\-on Python coding and system design assessments, covering machine learning fundamentals, model building, RAG, LLMs, agent\-based applications, LangGraph workflows , API development, and production deployment considerations (Docker, monitoring, traceability). Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: AI-ML Researcher Company: AkzoNobel Job Category: Machine Learning Roles & Responsibilities: Job Purpose The Technology Integration Team develops and productizes reusable Color Technology Components that power AkzoNobel’s internal applications and external customer\-facing tools, with focus areas in Colorimetric Engines/Building Blocks, Color Visualization, and AI/ML\-enabled color services. The AI/ML Researcher owns the delivery of applied Machine Learning and statistical solutions for prioritized color and coatings use cases (e.g., formulation optimisation, pigment/raw material screening, quality prediction, and image\-based inspection). The role translates business and R\&D questions into well\-structured datasets, validated ML models, and clear insights, and partners with engineering and product stakeholders to ensure solutions are deployment\-ready, monitored, documented and usable in products and processes. Unlike generalist Researcher roles, this position brings dedicated applied ML/data science capability to the team, owning the end\-to\-end ML lifecycle from problem framing through deployment\-ready model delivery. Key Accountabilities * Use case shaping \& stakeholder partnering * Engage with R\&D, lab teams, manufacturing and product/application stakeholders to translate needs into well\-defined ML problems, required inputs/outputs, constraints, and measurable success criteria. * Lead or co\-lead end\-to\-end delivery for assigned use cases from discovery and scoping through experimentation, validation, and implementation readiness. * Communicate trade\-offs (accuracy vs. explainability, latency, cost, robustness) and guide stakeholders toward fit\-for\-purpose solutions. * Data preparation, analysis \& modelling * Acquire, clean, integrate, and analyze data from R\&D/lab systems, manufacturing sources, and internal datasets; assess data quality, bias, leakage risk, and suitability for modelling. * Develop, benchmark, and validate ML models (supervised/unsupervised) including baseline creation, feature engineering, model selection, hyperparameter tuning, and robustness checks. * Domain application (color/coatings) * Collaborate with color formulators, researchers, and lab teams to ensure modelling aligns with domain realities (measurement variability, protocols, material constraints). * Define and drive dataset design/generation activities (e.g., DoE support, sampling strategy, labeling guidance, protocol awareness) to improve training data quality and coverage. * Apply practical understanding of relevant color data types (spectral/Lab\/ΔE and variability) when designing targets, features, and evaluation strategies (as applicable). * Computer vision (where relevant) * Deliver image\-based modelling tasks (e.g., defect detection, surface uniformity, pigment recognition) using classical CV and deep learning methods; define evaluation metrics and acceptance criteria aligned to operational deployment. * Ensure peer review and alignment with Senior Researchers/architects for high impact use cases and model choices that may affect product/process behavior. * Industrialization \& production readiness * Drive implementation readiness of assigned models: reproducible training/inference code, model artifacts, data dependencies, parameterization, testing approach, and clear runbooks. * Contribute to MLOps practices as defined by the team: version control, experiment tracking, model registry inputs, monitoring requirements, alert thresholds, and retraining triggers. * Partner with application/software teams to integrate model outputs into components/services (APIs, batch pipelines, or embedded usage) and support post\-deployment stabilization. At AkzoNobel we are highly committed to ensuring an inclusive and respectful workplace where all employees can be their best self. We strive to embrace diversity in a context of tolerance. Our talent acquisition process plays an integral part in this journey, as setting the foundations for a diverse environment. For this reason we train and educate on the implications of our Unconscious Bias in order for our TA and hiring managers to be mindful of them and take corrective actions when applicable. In our organization, all qualified applicants receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age or disability. Work Location: Bengaluru East, Karnataka, India Availability: Full time