We are looking for candidates, who build and ship machine learning systems, not just people who train models in notebooks. We are casting a wide net across the ML engineering spectrum, from research-leaning to production-leaning, because strong ML engineers come in many shapes.

The kind of skills that fit here (any combination, none required, all welcomed):

• Modeling — classical ML, deep learning, model selection, hyperparameter tuning, and evaluation
• Production ML — taking models from notebook to production: serving, scaling, latency and cost optimization
• Pipelines & infrastructure — feature stores, training pipelines, versioning (MLflow, DVC), reproducibility
• Engineering fundamentals — strong Python (or C++, Java, Go), software design, testing, and code quality
• Frameworks — PyTorch, TensorFlow, scikit-learn, ONNX, or equivalents
• Cloud & deployment — AWS/GCP/Azure, Docker, Kubernetes, GPU/inference optimization
• Data collaboration — working closely with data engineers and analysts on data quality and feature design
• Monitoring — model drift detection, A/B testing, performance tracking in production

Why this is worth your time

• Full-time employment, backed by reliable and time payroll.
• Compensation benchmarked above typical agency rates, leveraging full-time US/European working hours.
• Placement in high paying roles, matched directly to your profile. No searching, job boards, or sending out 100+ numericals.
• A single point of contact, who knows your track record, advocates for your worth, and pitches you directly to decision makers.
• Priority access to new roles, before they are opened broadly, with no obligation to accept any placement brought to you.

Every skill you bring is of value.

If any part of this list describes you, apply now!