AI/ML Engineer (all genders)

About the role

As an AI/ML Engineer, you will design, build, and maintain machine learning pipelines within Vertex AI. This involves covering the full lifecycle from training and evaluation to deployment, monitoring, and retraining. A key part of the role is developing GenAI capabilities, which includes working with embeddings, retrieval pipelines, vector databases, and RAG frameworks to support features like chatbots and semantic search.

The position also requires you to build and manage feature stores and datasets, collaborating with Data Engineers and Analysts. You will be responsible for productionizing workflows using Prefect orchestration and CI/CD pipelines in Bitbucket. This includes implementing continuous evaluation, drift detection, performance monitoring, and establishing rollback strategies for deployed models.

A crucial aspect of this role is embedding compliance standards like GDPR, RBAC, and anonymization into every model and pipeline. You will document the lineage of features, models, and inference workflows, and work with the Data Governance Lead on ethical AI frameworks. Success means translating technical capabilities into clear business outcomes and mentoring Data Engineers in ML Ops and GenAI techniques.

The annual salary for this position ranges from $65,000 to $95,000 USD.

Skills that matter here

• Python: Expert proficiency in Python is required for developing and maintaining ML and GenAI infrastructure.
• ML/DL libraries: You will use libraries like scikit-learn, TensorFlow, PyTorch, Hugging Face, and LangChain to build machine learning and deep learning solutions.
• Vertex AI: Hands-on experience with Vertex AI is necessary for pipeline orchestration, deployment, and monitoring of ML models.
• Prefect: You will use Prefect for orchestrating production workflows.
• vector databases: Experience with vector databases such as Pinecone, FAISS, or Milvus is needed for developing GenAI capabilities.
• SQL: Strong SQL skills, along with BigQuery and dbt, are essential for feature and data preparation.

Who this role suits

• You have 5 to 7 years of experience in Data Engineering or ML Ops, with at least 3 years focused on productionizing ML pipelines.
• You possess a degree in Computer Science, Data Science, Engineering, or a related field.
• You are a systems thinker with a strong ethical grounding in responsible AI, balancing innovation with operational reliability and cost control.
• You can effectively communicate technical concepts and trade-offs to non-technical stakeholders, translating AI/ML into measurable business outcomes.

From the employer

What you'll do

• Design, build, and maintain modular, reusable ML pipelines in Vertex AI Pipelines covering training, evaluation, deployment, monitoring, and retraining.
• Develop GenAI capabilities including embeddings, retrieval pipelines, vector databases, and RAG frameworks for chatbots, personalisation, and semantic search.
• Build and manage feature stores and reusable datasets in collaboration with Data Engineers and Analysts.
• Productionise workflows with Prefect orchestration and CI/CD pipelines in Bitbucket.
• Implement continuous evaluation, drift detection, performance monitoring, rollback strategies, and retraining triggers for deployed models.
• Embed GDPR compliance, RBAC, anonymisation, explainability, fairness, and auditability into every model and pipeline.
• Document lineage of features, models, and inference workflows, and partner with the Data Governance Lead on ethical AI frameworks.
• Translate technical capabilities into business friendly outcomes, communicating trade offs across accuracy, latency, and cost to non technical stakeholders.
• Mentor Data Engineers in ML Ops and GenAI techniques, and contribute to internal AI/ML guilds and best practices.

Your profile

• 5 to 7 years of experience in Data Engineering or ML Ops, with at least 3 years focused on productionising ML pipelines.
• A degree in Computer Science, Data Science, Engineering, or a related field. PhD a plus.
• Expert proficiency in Python and ML/DL libraries such as scikit-learn, TensorFlow, PyTorch, Hugging Face, and LangChain.
• Strong with BigQuery, dbt, and SQL for feature and data preparation.
• Hands-on experience with Vertex AI for pipeline orchestration, deployment, and monitoring (or AWS/GCP equivalents).
• Experience with Prefect orchestration and CI/CD pipelines in Bitbucket.
• Familiarity with ML Ops frameworks such as MLflow or TFX, and containerisation with Docker and Kubernetes.
• Experience with vector databases such as Pinecone, FAISS, or Milvus.
• Proven delivery of ML or GenAI use cases in production with measurable business impact.
• Strong stakeholder communication and the ability to translate AI/ML into measurable business outcomes.
• Systems thinker with strong ethical grounding in responsible AI; balances innovation with operational reliability and cost control.

What we offer

• An appealing discount on all of our products – from essential oils to vitamins & nutrients.
• The Urban Sports Club membership, Swapfiets bike rental and a subsidy for the BVG ticket.
• Your career is unique. That’s why we offer the opportunity for tailored Learning & Development as well as (Leadership) Coaching programs, designed to support your personal professional journey.