ML Engineer

Traffic during holiday peaks can reach ten times normal levels, and the platform is built for it. Our office has a quiet floor and a loud floor.

The role:

This is a new role. The team has doubled in size over the past year. Rudderwater is hiring for the ML Engineer role to take models from notebook to production and keep them working once they're there. You will be employed through our employer-of-record partner in the US, with a local contract and salary paid in USD. Few meetings, lots of written updates.

Essential duties and responsibilities:

• Deploy models behind low-latency APIs with FastAPI, Triton, TorchServe or vLLM.
• Orchestrate pipelines with Kubeflow, SageMaker Pipelines, Vertex AI or Airflow.
• Build training pipelines in PyTorch or TensorFlow and run them on GPUs in AWS, GCP or Azure.
• Fine-tune open-weight models with LoRA when it beats prompting.

Skills and experience:

• Strong Python and solid engineering habits (testing, packaging, code review)
• Comfortable with SQL and large-scale data processing in Spark or Ray.
• Understanding of core ML concepts: overfitting, evaluation metrics, bias in training data.
• Familiarity with Docker, Kubernetes and a cloud ML platform (SageMaker, Vertex AI, Azure ML)
• Hands-on experience with PyTorch, TensorFlow or JAX.

What you get:

• Annual team retreat.
• Annual learning budget.
• Home office setup budget.
• Wellness allowance.

We are an equal opportunity employer and value diversity. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

We are unable to sponsor visas for this position.

Start: Within 30 days.

Demo job created on 11jobs for testing and demonstrations. It is not an actual opening at Rudderwater.