AI ML Engineer

Work Location Noida/Bangalore/Chennai Detailed JD Expectation for all engineer profiles Foundational AI/ML & Software Engineering Strong grounding in ML fundamentals and software engineering, enabling translation of business problems into robust, scalable AI/ML solutions Experience in designing, building and integrating production-grade systems using modern engineering practices (APIs, microservices, CI/CD, containerization) Ability to bridge classical ML approaches with emerging GenAI paradigms, applying the right techniques to deliver reliable and maintainable solutions Effectively leverage AI-assisted development tools (e.g., GitHub Copilot, Claude Code) to accelerate prototyping, improve engineering quality and enhance developer productivity Product Collaboration & Enablement Ability to work effectively within agile product teams, collaborating in iterative cycles to refine requirements, validate hypotheses and deliver incremental AI/ML value Ability to drive alignment independently across product, AI/ML engineering, platform and MLOps teams to achieve shared engineering outcomes Strong capability in early-stage AI/ML solution development, including problem framing, feasibility assessment, rapid prototyping and iterative experimentation Effective collaboration across geographically distributed teams (Denmark, India, Portugal), with strong cross-cultural awareness and communication Profile Types: AI Engineer Specialist: 8-12+ years of experience in software engineering, data or analytics, with significant hands-on experience and demonstrated impact in AI/ML solution development, including 4-6+ years focused on AI/ML Senior Engineer: 5+ years of experience in software engineering, data or analytics, with strong hands-on experience in AI/ML solution development, including 2-4+ years focused on AI/ML AI/ML Engineer with focus on traditional ML (deep learning, CV) Profiles: Specialist [1] Responsibilities: Contribute to the development and deployment of ML, deep learning and computer vision solutions for industrial use cases across the Vestas value chain Build and enhance ML/DL/CV solution components, including pipelines and inference workflows, while developing and optimizing deep learning and computer vision models Integrate ML, deep learning and computer vision capabilities into enterprise applications and edge/cloud systems using APIs, microservices and containerized environments Collaborate with solution team to deliver reliable ML/DL/CV solutions end-to-end, contributing to development, testing and deployment while following engineering and MLOps standards Continuously learn and apply best practices in traditional ML, deep learning and computer vision, including advancements in model architectures, training techniques and deployment optimization Competencies: Traditional ML & Deep Learning Systems Engineering Ability to contribute to building scalable and reliable ML, deep learning and computer vision systems with focus on performance, robustness, data integrity and maintainability Understanding of standard design patterns and engineering practices for training, evaluating and deploying ML/DL models (including distributed training and efficient inference) Familiarity with deploying and integrating ML/CV solutions into production environments across cloud and edge systems ML, Deep Learning & Computer Vision Solution Development Hands-on capability in developing ML, deep learning and computer vision solutions for structured data, image/video data and industrial use cases Working knowledge of computer vision techniques such as object detection, image classification, segmentation and video analysis, along with deep learning architectures (CNNs, vision transformers, transfer learning and model optimization) Working knowledge of techniques such as feature engineering, model selection, hyperparameter tuning, transfer learning and model optimization (e.g., pruning, quantization) Ability to implement end-to-end ML workflows, including data preprocessing, model development, evaluation and deployment, with support for human-in-the-loop and decision-support systems AI/ML Engineer with focus on solution design, engineering and scaling from prototype to reliable, integrated production systems Profiles: Specialist [1], Senior Engineer [1] Responsibilities: Lead design, development, delivery and scaling of ML, LLM and agentic solutions to deliver measurable business impact across Vestas value chain Build and contribute hands-on to robust ML pipelines, workflows and modeling efforts, ensuring reproducibility, strong CI/CD integration, data/feature consistency and high standards for code quality, testing and deployment Drive integration of AI/ML capabilities into enterprise applications, enabling seamless adoption and value realization Own and drive system architecture decisions to ensure scalable, reliable, cost-efficient and maintainable AI/ML solutions Establish and promote reusable frameworks, patterns and engineering standards to improve team productivity and solution scalability across teams Competencies: Scalable AI/ML Systems & Deployment Engineering Productionize ML, LLM/GenAI models and agentic systems into reliable, high-performance services with optimized latency, throughput and cost efficiency Design, build and operate scalable batch and real-time ML pipelines for training & inference with strong reproducibility across environments Build and orchestrate automated end-to-end ML workflows, integrating CI/CD practices and ensuring data & feature consistency across environments Lead end-to-end productionization of AI/ML solutions, including enterprise integration via microservices, APIs and Docker based containerization Apply advanced MLOps practices, including scalable system design, production-grade engineering, ML governance and robust monitoring Manage full ML lifecycle, including versioning, governance, automated retraining and resilient deployment strategies Demonstrate hands-on expertise in Git/Azure DevOps and modern build/test/deploy tools, with experience in enterprise ML platforms (e.g., Databricks MLflow, AI Foundry) Skills: Deep Learning, Ml, Ai, Python Experience: 6.00-15.00 Years