Senior Machine Learning Engineer (NLP & GenAI) to Vestas AI CoE

Do you want to leverage NLP, genAI, and ML engineering to help change our planet's trajectory?  Are you passionate about designing, developing, and implementing impactful and scalable NLP and genAI solutions?  Do you enjoy working in a fast-paced, collaborative environment, partnering with both business and technical stakeholders across the company? Then you might be the new colleague we are looking for in our newly established AI Center of Enablement (CoE) in Vestas Digital Solutions.
 

 Digital Solutions > Data & Enterprise Architecture  > AI Center of Enablement 
The AI Center of Enablement aims to partner across the organization to raise the bar for what we can achieve with machine learning (ML). We help deliver impactful solutions across the value chain from research, turbine design, commercial, manufacturing, supply chain, and service. We want to ensure the scalability and accessibility of ML, reduce the time-to delivery from PoC to production with the creation of efficient processes and frameworks for spotting and qualifying opportunities, creating reference architectures, MLOps frameworks, and modularized components that span across the ML lifecycle.  We are on a cloud journey and are working primarily in Azure across a data science tool stack that currently includes Dataiku, Databricks, Snowflake, and AzureML. We work agile and aim to build a passionate and dedicated team with a culture of collaboration, continuous learning, and - not to forget - a lot of fun. 

Our AI CoE is part of Vestas newly established Digital Solutions organization set to drive end-to-end digitalization of Vestas over the coming years. As part of the Data Products and Platform Area, we co-build with product delivery teams within and beyond Digital Solutions to leverage cross-functional competences for impactful ML solution delivery. In addition, we are working closely with our Data Platform team to mature our platform capabilities, shape our MLOps framework, and ensure the scalability of our data science platforms and ML tool stack.

 

Responsibilities

You will work together with business leaders and experts, data scientists, and data engineers across the organization to build ML solutions with a specific focus on LLM/genAI based solutions. The position is a senior role with a significant amount of informal leadership and responsibility for accelerating and scaling the impact of AI across Vestas. 
You will:

• Develop and productize ML algorithms, NLP, and genAI to impact and accelerate business value across Vestas' value chain
• Proactively identify use cases and improve modelling approaches, libraries, and methods that can scale ML and genAI across the organization
• Lead the development of reference architectures and frameworks for designing and deploying NLP- and LLM-based solutions 
• Evangelize best practices and co-build with less experienced data scientists in the field
• Cooperate across data science, data engineering, and cloud infrastructure to accelerate solution delivery and mature our platforms and tool stack for leveraging NLP and genAI
• Do vendor and solution assessments on both tools for custom development and off-the shelf AI solutions
• Contribute to shaping our new AI CoE organizationally and culturally making it a highly impactful unit and a delightful home to our team

 

Qualifications
This role is for you if you have a deep understanding of machine learning and NLP methods, have done your share of exploration within the genAI space, and have solid software development, communication, and collaboration skills.  We are looking for a senior profile who masters the generalist applied ML toolbox necessary to drive AI solutions from idea to production while being agenda setting within the NLP and genAI area.
We are thus looking for many or most of the qualifications and competences below:

• 5+ years of experience deploying and implementing NLP-based solutions
• Background in a quantitative field, e.g., Computer Science, Physics, Mathematics, Engineering, Economics
• Deep knowledge of Python, ability to develop production grade code, and solid experience with frameworks for Machine Learning (i.e. scikit-learn, Tensorflow, PyTorch) and NLP (e.g.  NLTK, SpaCy, Hugging Face Transformers, LangChain, LlamaIndex)
• Experience working with LLMs and use cases centering around genAI, including aspects such as cost optimization, finetuning vs. prompt engineering, evaluation of LLM performance etc. 
• Hands-on experience in designing and implementing in cloud (ideally Azure) deploying with CI/CD and working with modern build, test, and deployment tools
• Experience with RESTful APIs and containerization using Docker
• Strong communication skills and ability to collaborate closely with business and technology func