ML Engineer (NLP & GenAI)

Vestas is well-known in wind technology and actively contributes to its development. Vestas core business comprises the development, manufacture, sale, marketing, and maintenance of Wind Turbines. Come and join us at Vestas! At the core of Data & AI organization, the AI/ML Chapter serves as the capability home for AI/ML, supporting craft excellence, skills development and scalable delivery practices across Vestas. With a global footprint spanning India and Denmark, the team partners closely with product owners and engineering teams to build and scale AI/ML solutions embedded in digital products across the value chain. The chapter focuses on building and scaling AI/ML capabilities for high-value and autonomous flow use cases, providing consistent know-how across product areas, ensuring readiness for emerging paradigms such as LLMs and agentic AI, and enabling scalable delivery through a balanced mix of internal capability development and strategic partnerships. Through solid engineering, data-centricity, and close business collaboration, the team advances AI/ML delivery practices and enables impactful solutions that improve visibility, optimization and innovation across the enterprise. ResponsibilitiesAs part of the product team, you will collaborate with product owner, ML engineers, application developers and business SMEs to develop and scale GenAI and agent-based capabilities within digital products. This role focuses on active development, learning, and contributing to valuable AI solutionsContribute to the design, development and deployment of GenAI and agentic systems supporting reasoning, planning, and semi-autonomous workflowsBuild and enhance components of GenAI solutions using LLMs, RAG pipelines, prompt engineering and tool integrationDevelop intelligent workflows using techniques such as prompt engineering, context orchestration and function/tool callingIntegrate GenAI capabilities into enterprise applications using APIs, microservices, and containerized environmentsCollaborate with senior AI engineers to implement scalable, reliable GenAI systems and follow established design patterns and standardsParticipate in end-to-end delivery of GenAI initiatives, contributing to development, testing and deploymentContinuously learn and adopt best practices in GenAI, NLP, and agentic systems developmentQualificationsAI/ML Solutions ExperienceBachelor's or Master's degree in Computer Science / Engineering / Data Science / or similar specialization6+ years of experience in AI/ML, software engineering, data or analytics, focusing on digital solutions development2-5 years of core experience in AI/ML solution development, ML engineering, with a focus on NLP and applied GenAI systemsPractical experience with LLM ecosystems (e.g., OpenAI, Azure OpenAI, open-source models), including prompt engineering and basic context designPractical experience with RAG architecture, embeddings or vector databasesExperience building and integrating applications using APIs, microservices or containerized environmentsFamiliarity with software engineering best practices (version control, testing, CI/CD basics)Exposure to agentic workflows, including tool usage, chaining, or multi-step reasoningFamiliarity with LLM evaluation concepts and basic understanding of LLMOps practices such as monitoring, versioning, and cost awarenessAbility to contribute to building scalable and reliable GenAI systems with focus on performance and maintainability o Understanding of standard design patterns and engineering practices for LLM-based applicationsFamiliarity with deploying and integrating GenAI solutions into production environmentsGenAI & Agentic Solution DevelopmentPractical experience in developing GenAI and agent-based solutions for structured workflows and assisted decision-makingWorking knowledge of techniques such as RAG, prompt engineering and tool integrationAbility to implement intelligent workflows combining human-in-the-loop and automated processes under guidanceFoundational AI/ML & Software EngineeringSolid foundation in ML concepts and software engineering principles for building maintainable systemsExperience developing and integrating services using APIs, microservices and modern engineering practicesProficiency in leveraging AI-assisted development tools (e.g., GitHub Copilot, Claude Code) to improve productivity and code qualityAbility to collaborate effectively within distributed teams across geographiesSolid teamwork skills working with senior engineers and cross-functional stakeholdersDemonstrates a continuous learning mindset with interest in GenAI, NLP and agentic systemsWhat We OfferPurpose -An opportunity to help address climate change and support future generations through building AI/ML, GenAI and agentic solutions that power the future of renewable energy and sustainable operations Accelerated learning & growth -Join a high-caliber global team of AI/ML engineers, data scientists and GenAI practitioners, with a V