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Salary analysis
Compared with the selected benchmark ("Market Average: Machine Learning Engineer"), this listing's salary midpoint is about 3% higher. The offer still falls within the benchmark range (€11,159–€21,189). The listed pay band (€14,143–€19,134) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 3 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 |
| Pay in our data — not quoted in ad (Mid-Level) | €14,143/per month | €16,639/per month | €19,134/per month |
An ML engineer at IFS is part software engineer, part dev ops engineer and ML savvy, who combines knowledge of systems and applications, machine learning and artificial intelligence to build and deploy AI-driven solutions. The work is focused on designing and maintaining high-performance, scalable AI/ML infrastructure, building, and executing ML pipelines efficiently, serving models at scale, and creating the tools for continuous monitoring and improvements. Someone in this role uses their technical know-how to translate high-value and innovative AI opportunities into deployable and sustainable products. ML engineers are well-versed on AI/ML techniques, ranging from statistical learning, computer vision to generative AI. They have strong foundations in software engineering, ML algorithms and mastered several AI/ML serving frameworks. ML engineers work in close collaboration with data scientists, data engineers, architects, and DevOps engineers, on the creation and deployment of highly scalable infrastructure and AI-driven solutions. In addition, ML engineers at IFS continuously expand their knowledge of AI infrastructure, model monitoring/observability and drift detection, functional and business process domain knowledge and share this knowledge to guide others.
Job Details
Requirements
- Vahva osaaminen Pythonissa ja kokemus relevantteistä kirjastoista (NumPy, Pandas, Kserve, jne.)
- Tietämys lisäkielistä kuten Go, C# tai SQL on plussaa
- Tuttavuutta pilvipalveluiden (Azure), Infrastructure as Code:n (terraform, helm charts), CI/CD:n, Git Ops:n ArgoCD:n ja konttiteknologioiden (Docker, Kubernetes) kanssa
- Perustiedot koneoppimisen käsitteistä, mukaan lukien valvottu ja valvomaton oppiminen, syväoppiminen ja mallin arviointitekniikat
- Dataesikäsittelyn ja ominaisuuksien muokkaamisen osaaminen. Kokemus relaati- ja vektoritietokannoista.
- Erinomaiset analyyttiset taidot, kyky tulkita monimutkaisia tietojoukkoja ja johtaa toimenpiteisiin perustuvia oivalluksia.
- Erinomaiset suulliset ja kirjalliset viestintätaidot, kyky tehdä tehokasta yhteistyötä poikkitoiminnallisten tiimien ja sidosryhmien kanssa
- Kandidaatin tai maisterin tutkinto tietojenkäsittelytieteessä, ohjelmistoinsinööritieteessä, data science -alalla tai vastaavassa, vähintään 3+ vuoden kokemus ohjelmistokehityksestä, mukaan lukien kokemusta AI/ML-kehitysympäristöistä kuten TensorFlow, PyTorch tai scikit-learn.
Education Level
No degree required
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