Take machine learning use cases from prototype to maintainable production systems.
What you'll do
- Build data and ML pipelines with reproducible training and evaluation.
- Integrate models and LLM features into client products with guardrails.
- Implement MLOps: versioning, monitoring, and drift detection.
- Translate business problems into measurable ML outcomes.
What we're looking for
- Experience deploying ML systems to production.
- Strong Python and data engineering fundamentals.
- Familiarity with MLOps tooling and cloud ML services.
- Pragmatic approach to model selection and evaluation.
What we offer
- Flexible work: Remote-first culture with hubs in Milan and Sofia. Work where you perform best.
- Real impact: Ship to production on meaningful systems — not endless internal tooling with no users.
- Learning budget: Conference attendance, certifications, and training aligned to your growth path.
- Modern stack: Current cloud, security, and engineering practices — not legacy maintenance by default.
How to apply
Send your CV and a short note explaining why this role interests you and what you'd want to build at TechForge.
Include links to GitHub, portfolio, or relevant projects if you have them. We read every application and reply
to those that look like a strong fit — typically within one week.
