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Vestas

Lead Specialist, Machine Learning Engineer

Vestas is hiring a Lead Specialist, Machine Learning Engineer. Level rates it ; you can apply on Vestas.

Level's read on this job

  • Level rates this machine learning engineer role Builds AI ●●●●: the job is building AI systems.
  • The posting mentions Claude, Copilot and LangChain among its tools and skills.
  • Level classes it as a lead role.
  • Vestas has 668 other open roles on Level.
  • Posted within the past two weeks.

AI in this role

claudecopilotlangchainlanggraphpytorchtensorflowscikit-learnclaude-code
ai-agentsml-opsai-automationcomputer-visionnlp

 

Specialist | Full-Time

Digital Solutions & Development > Digital Solutions > AI/ML Chapter

 

At the core of the Digital Development Platform organization, the AI/ML Chapter serves as the capability home for AI/ML specialization, supporting engineering excellence, skills development, and scalable delivery across Vestas. You will be part of a global team spanning Denmark and India, partnering closely with product owners, AI/ML engineers and business stakeholders to design, build, and scale AI/ML, GenAI, and agentic solutions across the value chain from R&D and manufacturing to supply chain and service.

The chapter focuses on building and scaling AI/ML capabilities for high-value and autonomous flow use cases. It provides consistent knowledge across product areas, ensures readiness for emerging paradigms such as LLMs and agentic AI, and enables scalable delivery through a balanced mix of internal capability development and strategic partnerships. With disciplined engineering practices, data-focused methods, and close collaboration with business partners, the team continually raises AI/ML delivery standards and enables meaningful solutions that improve visibility, optimization, and innovation across the enterprise.

As part of the broader Autonomous Flows initiative, the team contributes to building next-generation intelligent systems and agentic workflows that enhance operational efficiency and unlock new business value. We collaborate closely with platform, product and governance teams to ensure scalable, responsible, and impactful adoption of AI across Vestas.

 

Responsibilities

 

  • As a senior member of the product team, you will collaborate with product owners, AI/ML engineers, developers and business stakeholders to build and scale AI/ML capabilities in digital products. The role involves effective informal leadership with a focus on accelerating delivery and increasing business impact
  • Oversee the design, delivery and scaling of ML, GenAI and agentic solutions to deliver measurable business impact across Vestas value chain
  • Implement the integration of AI/ML capabilities into enterprise applications, enabling seamless adoption and value realization
  • Establish and promote reusable patterns and engineering standards for scalable delivery, AI-ready data, and trusted AI automation
  • Own the end-to-end delivery across multiple initiatives, balancing speed, quality and evolving priorities
  • Partner with stakeholders on AI/ML strategy, guiding solution design aligned with business goals and governance standards

 

Qualifications

 

You have a solid foundation in machine learning and software engineering, combined with clear communication and stakeholder engagement skills. You bring extensive experience in designing and scaling production-grade AI/ML systems, with experience leading solutions across the full lifecycle from problem framing to deployment and continuous improvement. You have demonstrated depth in fields such as NLP, generative AI, agentic systems, computer vision, ML engineering, or large-scale AI systems.

 

  • AI/ML Solutions Experience: A master's degree in a relevant field (e.g., computer science, data science, engineering) or equivalent practical experience, 8+ years of experience in ML engineering, with experience in designing, delivering, and scaling production-grade AI/ML solutions
  • Deep knowledge of Python, ability to develop production grade code, solid experience with ML frameworks (e.g., Scikit-learn, Tensorflow, Pytorch) and GenAI/Agentic frameworks (e.g., Langchain, LangGraph, Pydantic AI)
  • Deep experience with AI experimentation and modeling, as well as designing robust, scalable training and inference pipelines on cloud platforms including Azure and Snowflake, deployed through CI/CD within an IaC environment.
  • Solid experience with RESTful API design, Docker-based containerization, and Kubernetes-based deployment, scaling, and operations.
  • Extensive experience in MLOps, with a focus on scalable architecture, governance, production engineering, and detailed monitoring of model, data, and system performance

 

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 and operate scalable batch and real-time ML pipelines with high reproducibility across training and deployment
  • Establish robust monitoring and observability for model performance, data quality, system health and data drift detection
  • Manage the full ML lifecycle with clear versioning, governance, automated retraining and resilient deployment strategies
  • Effectively leverage AI-assisted development tools (e.g., GitHub Copilot, Claude Code) to accelerate prototyping, improve engineering quality and enhance developer productivity in building AI/ML and GenAI solutions

 

Global Collaboration & Enablement

  • Effective collaboration across geographically distributed teams (Denmark, India, Portugal), with high cross-cultural awareness and communication
  • Ability to align product, AI/ML engineering, platform and MLOps teams to deliver shared engineering outcomes
  • Demonstrated experience in mentoring and enabling teams through knowledge sharing, best practices and informal leadership

 

What We Offer

Purpose. 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 and growth. Join a high-caliber global team of AI/ML engineers, data scientists and GenAI practitioners, with clear focus on continuous learning, knowledge sharing and expanding into agentic autonomous flows.

Global collaboration & collaborative team culture. Work within a multicultural Denmark-India setup that values trust, collaboration and mutual support to deliver meaningful impact.

Opportunity to shape your role. Play a key role in scaling agentic autonomous flows and high-value AI/ML solutions, with the freedom to shape direction, approaches, and outcomes.

Supportive and inclusive environment. Thrive in a diverse, inclusive workplace that promotes well-being, work-life balance and enables individuals to bring their full potential to work.

Career growth in a global organization. Join a global organization that supports ongoing skill development and career advancement

Overall, we offer you the opportunity to contribute meaningfully while growing your career in a global, multicultural environment that promotes continuous learning and development.

BEWARE – RECRUITMENT FRAUD
It has come to our attention that there are a number of fraudulent emails from people pretending to work for Vestas. Read more via this link, www.vestas.com/en/careers/job-openings.

DEIB Statement
At Vestas, we recognize the value of diversity, equity, and inclusion in driving innovation and success. We strongly encourage individuals from all backgrounds to apply, particularly those who may hesitate due to their identity or feel they do not meet every criterion. As our CEO states, "Expertise and talent come in many forms, and a diverse workforce enhances our ability to think differently and solve the complex challenges of our industry". Your unique perspective is what will help us powering the solution for a sustainable, green energy future.

About Vestas
Vestas is the energy industry’s global partner on sustainable energy solutions. We are specialised in designing, manufacturing, installing, and servicing wind turbines, both onshore and offshore.  Across the globe, we have installed more wind power than anyone else. We consider ourselves pioneers within the industry, as we continuously aim to design new solutions and technologies to create a more sustainable future for all of us. With more than 173 GW of wind power installed worldwide and 40+ years of experience in wind energy, we have an unmatched track record demonstrating our expertise within the field.  With 29,000 employees globally, we are a diverse team united by a common goal: to power the solution – today, tomorrow, and far into the future.  Vestas promotes a diverse workforce which embraces all social identities and is free of any discrimination. We commit to create and sustain an environment that acknowledges and harvests different experiences, skills, and perspectives. We also aim to give everyone equal access to opportunity.  To learn more about our company and life at Vestas, we invite you to visit our website at www.vestas.com and follow us on our social media channels. We also encourage you to join our Talent Universe to receive notifications on new and relevant postings. 

How we rate this

Lead Specialist, Machine Learning Engineer at Vestas rates 91 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsML OpsAI AutomationComputer visionNLPClaudeCopilotLangChain

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$200k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. How do you monitor a model once it's live, and how do you know it needs retraining?
  3. Tell me about a workflow you automated with AI tools, end to end.
  4. Walk me through a computer vision problem you solved, from raw data to a deployed model.
  5. What NLP problem have you worked on, and how did you measure whether it actually worked?

Adapt your resume

  • List these exact terms on your resume: AI agents, ML Ops, AI Automation, Computer vision, and NLP. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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