ML Product Engineer

kausable

. Turn research models into production-grade services with clear reliability, latency and cost targets .

Posted 10/8/2026full-timeHeidelberg • GermanyMid-LevelSenior💰 €55,000 - €120,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying ML-powered systems, with a strong focus on Python programming, PyTorch proficiency, and effective model serving. Capable of translating customer needs into robust platform capabilities while ensuring reliability and observability in production environments.

Highest-signal resume keywords

ML-Powered Systems DeploymentPython ProgrammingPyTorch ProficiencyModel Serving and APIsCloud Infrastructure Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningSoftware EngineeringData Pipeline DesignModel EvaluationModel VersioningAPI DevelopmentObservabilityReliability EngineeringContainerizationMLOps Tooling

Soft Skills

Pragmatic MindsetOutcome-Oriented ApproachCollaboration with StakeholdersJudgment in Production Trade-offs

Tools & Technologies

Weights & BiasesModel RegistriesCI for ModelsSDK DesignDeveloper-Tooling

Industry Keywords

Production-Grade ServicesModel Release ManagementCustomer Feedback IntegrationOn-Premise DeploymentSynthetic Data

Tech Stack

Tools & technologies

CloudPythonPyTorch

About the role

Key responsibilities & impact

Turn research models into production-grade services with clear reliability, latency and cost targets
Build evaluation harnesses and release criteria to quantify when a model is ready to ship
Design data pipelines, versioning and observability across training, evaluation and live inference
Build stable APIs and developer-facing abstractions around the models
Work with researchers to expose failure modes and turn product feedback into better models and evaluations
Translate customer and design-partner needs into reusable platform capabilities
Own model releases, monitoring and rollback patterns as the production footprint grows

Requirements

What you’ll need

Track record of shipping ML-powered systems to production and operating them after launch
Strong software engineering skills in Python
Hands-on fluency with PyTorch
Experience with model serving, APIs, containers and cloud infrastructure
Sound judgment around evaluation, observability, reliability and production trade-offs
Ability to work directly with customers, researchers and product stakeholders
Pragmatic, outcome-oriented mindset
Primarily hiring at senior level
Exceptional candidates with fewer years of experience may be considered if they demonstrate comparable depth, judgment and ownership
Nice to have: In-context learning, PFNs, synthetic data or probabilistic models
Nice to have: Weights & Biases, model registries, CI for models or comparable MLOps tooling
Nice to have: SDK or developer-tooling design
Nice to have: Security, privacy or on-premise deployment requirements
Nice to have: Prior startup, design-partner or 0-to-1 product experience

Benefits

Comp & perks

VSOP equity: a real stake in what we build
30 days of paid holiday per year
Statutory social insurance
Conference travel and role-relevant learning
Flexible hybrid work, with roughly one in-person team meet-up per month
A high-end laptop
Access to the cloud compute required for the role
Opportunity for technical ownership of the model-to-product stack or leadership of a small ML product group as the team grows