
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("All roles in Helsinki, Finland"), this listing's salary midpoint is about 71% lower. The offer sits below the benchmark range (€2,070–€5,000). The listed pay band (€868–€1,160) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 2534 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| Market Average: Machine Learning Engineer | €11,159/per month | €16,639/per month | €21,189/per month |
| All roles in Helsinki, Finland | €2,070/per month | €2,907/per month | €5,000/per month |
| Pay in our data — not quoted in ad (Senior) | €868/per month | €1,014/per month | €1,160/per month |
Are you passionate about shaping the future of insurance technology? We are looking for a Senior ML Engineer who can turn machine learning from promising prototypes into reliable production services and help build long-term technical quality in a regulated business environment. Welcome to Nordea Life & Pension Finland. We are a solvent Finnish life insurance company and part of the Nordea Group... Now we focus on building our AI capability over maintaining a legacy. You'll join alongside data scientists, developers, and MLOps. Technical ownership, including architecture, standards and engineering direction, belongs to the senior engineers we're bringing in. What you’ll be doing: - Own the production lifecycle of ML/AI models: serving, monitoring, scaling and reliability - Design and operate model serving infrastructure (vLLM or equivalent) across hybrid environments - Implement ML-specific monitoring: prediction quality, drift detection, latency, throughput, and cost per inference - Manage GPU infrastructure: provisioning, scheduling, utilization optimization - Ensure security, compliance, and reliability for AI workloads in a regulated environment Our AI workloads include LLM serving on vLLM with GPU infrastructure, agent-based systems, and we use SageMaker for parts of our ML pipeline. The broader stack is Python, AWS, Docker, Kubernetes, Terraform, Jenkins, and Git. Who you are - Experience running ML/AI models in production - Strong Python skills for production systems - Strong understanding of why ML systems fail in practice: drift, data quality, silent degradation - Hands-on experience with Docker and cloud infrastructure, ideally AWS - Familiarity with model serving concepts: latency, reliability, scaling - Working proficiency in Finnish and English - Master’s or PhD in a related field What we offer - High autonomy and ownership - Real influence on architecture and engineering standards - Hybrid working: 60 % onsite and 40 % remote - Lunch (on top of salary), sport & culture benefit - Banking benefits e.g. personnel mortgage margin and free daily banking services - Modern office above metro station and close to train station - Training and education possibilities
Job Details
Responsibilities
- Own the production lifecycle of ML/AI models: serving, monitoring, scaling and reliability
- Design and operate model serving infrastructure (vLLM or equivalent) across hybrid environments
- Implement ML-specific monitoring: prediction quality, drift detection, latency, throughput, and cost per inference
- Manage GPU infrastructure: provisioning, scheduling, utilization optimization
- Ensure security, compliance, and reliability for AI workloads in a regulated environment
Requirements
- Experience running ML/AI models in production
- Strong Python skills for production systems
- Strong understanding of ML system failures in practice (drift, data quality, silent degradation)
- Hands-on experience with Docker and cloud infrastructure, ideally AWS
- Familiarity with model serving concepts: latency, reliability, scaling
- Working proficiency in Finnish and English
- Master’s or PhD in a related field
Skills & Technologies
Education Level
MastersBenefits & Perks
Recruitment Process
- 1Application submission
- 2Call with future team members

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