Engineer AI Amsterdam

Akzonobel IT is in the middle of a changing and modernizing IT function, and AI is in the middle of this change. We are forming an AI / ML team from scratch, supported by a central, global data platform, an organization that is rife with opportunity and a business that is actively looking for ways to act on AI related use cases they see. Akzonobel being the large multinational manufacturer of paints and performance coatings that it is, operating in industry and consumer markets, you can imagine that there is a lot to do in areas like digital marketing, (Gen)AI Q&A based assistance, price, margin and stock management, R&D, coat lifetime prediction and many more.

Are you that ML technical expert who enjoys getting their hands dirty and explore unchartered territory AND using the latest best practices in MLOps to set solid standards to get those new opportunities deployed in a lasting and valuable way? Then keep reading!

Our AI team is part of the Data & Analytics domain in IT Delivery, where we deliver data and analytics products from our Akzonobel Data Fabric, a centralised, global platform leveraging Databricks on Azure, as well as MS Fabric as an exposure layer, in a medallion architecture. Of course our primary focus is to bring value to our business, but a driving principle behind this is that we use an agile, iterative approach to prevent rework and replication and optimise for effective deployment, reuse and scalability. 

We are looking for an enthusiastic Functional Engineer AI who is not only excited about building high performing ML models and solving complex analytical problems, but also about applying and deploying their solutions in a dependable, consistent and lasting way that adds value to our business. You should have a solid background in development, integration, testing and deployment of ML models and ML/GenAI pipelines. 
 

•    Collaborate with business, architects and demand and project managers to understand company needs and devise possible AI / model based solutions.
•    Build scalable AI solutions in a cloud environment (Databricks) using python and Apache spark.
•    Develop projects through proof-of-concept, pilot and full deployment phases.
•    Further develop the AI components in our data platform to improve our technical infrastructure, standards of working and tool stack.
•    Integrate the final model with other aspects of the application; design and control how they communicate with one another (REST APIs, database queries, etc..).
•    Communicate results and ideas to key stakeholders; explain complex use cases at an appropriate level for the audience using effective data visualization techniques.
•    Experiment with new ideas, technologies and data to stay posted on the latest developments and identify new use cases to leverage them.

•    MSc in mathematics, statistics, computer science or related field; PhD degree (preferred) OR equivalent experience.
•    Ability to solve complex analytical problems using quantitative approaches with a unique blend of analytical, mathematical and technical skills.
•    Excellent understanding of machine learning techniques and algorithms, including LLM’s, but with a solid foundation in ‘traditional’ predictive modelling.
•    Strong data-oriented scripting (SQL), statistical programming (pref. python), big data frameworks (pref. Spark) and model governance (pref. MLFlow)
•    Experience with cloud technologies, preferably Azure stack, including LLM related services
•    Strong knowledge of and experience with MLOps and related data engineering principles (CI/CD, testing, documentation, ML governance, performance management).
•    Proven track record over multiple aspects of the end-to-end machine learning life cycle from proof of concepts to scalable solutions in production.
•    Experience with data visualization tools (PowerBI, Streamlit)
•    Good stakeholder management and communication skills.

It’s a two-way street. This means that we offer not only a competitive salary but also believe in a healthy work-life balance.
•    Above average number of annual holidays: 46 days
•    Participation in the AkzoNobel pension plan.
•    Fixed bonus 
•    Travel expenses to and from work.
•    Opportunities for ongoing education and professional development.
•    Hybrid way of working (60/40).
•    Being part of events and networking platforms.
•    Paint with a discount.

We aim to create a sense of belonging, where everyone can share their diverse backgrounds, participate in events, and connect through networking platforms.

We welcome your online application via .

The recruitment process includes a selection of the best applications received through the system, interview rounds and further steps. An online assessment and an employment screening might be part of the selection process.

If you have questions about the role or interview process, please contact Berber Wegener at via de button "Solliciteer nu" op deze pagina.