Python ML Engineer Needed
Budget: $250 – $750 USD
I’m leading the digital programme at a German construction company and we’re replacing a tangle of spreadsheets with a unified, API-driven platform for data analysis and reporting. Your main mission is to implement the calculation engines that power our new cost-estimation service and to embed them in production-ready FastAPI micro-services.
Tech landscape
• Python 3.11, FastAPI, Pydantic v2
• LightGBM, XGBoost and Prophet for the predictive bits
• PostgreSQL 15 with pgvector extensions for feature storage
• Celery & Redis for asynchronous workloads
• Everything ships as Docker containers, built and deployed via GitLab CI
What you’ll do
– Translate the specification and signed API contracts into clean, tested, well-documented code
– Design and implement cost-estimation models, plus supporting data pipelines and calculation logic
– Optimise queries and vector operations in PostgreSQL
– Package the service, write Helm-friendly Dockerfiles, and hand over a one-command local dev environment
Deliverables
1. Source code with ≥90 % unit-test coverage
2. Docker image and compose stack for local run
3. Auto-generated API docs (OpenAPI)
4. Short setup & operations guide (Markdown)
Acceptance criteria
• All endpoints pass the supplied Postman test suite
• Model accuracy meets or exceeds the baselines stated in the spec
• CI pipeline builds, tests and pushes the image without manual steps
To apply, show me past work that demonstrates the mix of Python, FastAPI, and ML in a production context. A link to a public repo or a concise write-up of a private project is perfect. Domain experience in engineering or manufacturing will definitely help you stand out.
Looking forward to seeing how you’d tackle this modernisation effort!
Tech landscape
• Python 3.11, FastAPI, Pydantic v2
• LightGBM, XGBoost and Prophet for the predictive bits
• PostgreSQL 15 with pgvector extensions for feature storage
• Celery & Redis for asynchronous workloads
• Everything ships as Docker containers, built and deployed via GitLab CI
What you’ll do
– Translate the specification and signed API contracts into clean, tested, well-documented code
– Design and implement cost-estimation models, plus supporting data pipelines and calculation logic
– Optimise queries and vector operations in PostgreSQL
– Package the service, write Helm-friendly Dockerfiles, and hand over a one-command local dev environment
Deliverables
1. Source code with ≥90 % unit-test coverage
2. Docker image and compose stack for local run
3. Auto-generated API docs (OpenAPI)
4. Short setup & operations guide (Markdown)
Acceptance criteria
• All endpoints pass the supplied Postman test suite
• Model accuracy meets or exceeds the baselines stated in the spec
• CI pipeline builds, tests and pushes the image without manual steps
To apply, show me past work that demonstrates the mix of Python, FastAPI, and ML in a production context. A link to a public repo or a concise write-up of a private project is perfect. Domain experience in engineering or manufacturing will definitely help you stand out.
Looking forward to seeing how you’d tackle this modernisation effort!