Senior Machine Learning Engineer
Novo Nordisk20 hours ago
Måløv, DenmarkSenior
Responsibilities
- Design, build, deploy, maintain, and operate machine learning models, LLM applications, and AI agents.
- Develop batch and real-time inference services integrated with business applications.
- Build training, evaluation, deployment, monitoring, and model-governance workflows with Databricks and MLflow.
- Operate AI infrastructure on AWS and Azure while balancing performance, reliability, security, and cost.
- Establish MLOps, LLMOps, AgentOps, and DataOps practices covering versioning, automated testing, rollback, safety controls, human oversight, and governed data.
- Monitor model quality, data drift, latency, availability, and cost; investigate failures and define evaluation criteria.
- Lead technical design discussions, review code, mentor engineers, and document operational procedures.
Requirements
- Bachelor-level degree in computer science, engineering, mathematics, or a related field, or equivalent practical experience.
- Typically 5+ years of experience in machine learning engineering, software engineering, or applied AI, including ownership of production ML systems.
- Strong hands-on Databricks expertise, including Python, PySpark, Spark SQL, Delta Lake, MLflow, production pipelines, model serving, workflow orchestration, and Unity Catalog governance.
- Practical experience deploying and operating ML or AI workloads on both AWS and Azure.
- Experience with Git, CI/CD, containers, and infrastructure as code such as Terraform.
- Implementation experience across MLOps, LLMOps, AgentOps, and DataOps, including reproducible training, model registries, rollback, retrieval-augmented generation, safety testing, agent tracing, tool permissions, data contracts, and lineage.
- Strong Python and SQL skills, solid machine learning fundamentals, and experience with scikit-learn, PyTorch, or TensorFlow.
- Experience building LLM applications with embeddings, retrieval, structured outputs, and tool calling.
- Experience with observability, incident response, production support, data privacy, security, responsible AI, and model governance.
- Ability to explain technical trade-offs, lead technical discussions, and mentor colleagues.
- Preferred qualifications include experience with Azure Machine Learning, Azure AI services, Amazon SageMaker, Amazon Bedrock, Kubernetes, GPU workloads, distributed training, feature stores, vector search, fine-tuning, agent orchestration frameworks, evaluation frameworks for probabilistic systems, regulated or security-sensitive AI environments, and relevant Databricks, AWS, or Azure certifications.
Benefits
- Annual base salary of 651,000 to 956,900 DKK, with placement based on skills, competencies, knowledge, and relevant experience.
- The package may include short-term and/or long-term incentives and other employee benefits based on position level, location, functional area, and market benchmarks.
- Access to on-the-job growth and relevant learning offerings in a culture with clear performance expectations and feedback.
- Applications are reviewed on an ongoing basis, with an application deadline of 22 October 2026.