👉Senior ML Engineer (AI/ML Platform)

🟣 You will be:

• developing scalable ML solutions by applying software engineering best practices and transforming exploratory code into modular, reusable, and testable Python packages,

• implementing experiment tracking, reproducibility, and versioning practices to ensure traceability of ML workflows and results,

• designing and building distributed training pipelines with robust checkpointing, fault tolerance, and standardized model evaluation frameworks,

• creating production-ready model packaging, serving, and deployment solutions, including versioned containers, canary releases, rollback procedures, and online/batch inference,

• building and maintaining ML monitoring and retraining pipelines covering data drift detection, prediction quality monitoring, and continuous model evaluation,

• defining and enforcing ML lifecycle governance, including observability, documentation, operational runbooks, and model retirement processes,

• collaborating with cross-functional teams while taking ownership of ML engineering deliverables and promoting security-first engineering practices.
  

🟣 Your profile:

• proven experience as an ML Engineer in production environments,

• strong proficiency in Python and modern ML frameworks (TensorFlow, PyTorch),

• hands-on experience with: ML lifecycle tooling (MLflow, Vertex AI, or equivalent), distributed training and scalable compute environments, containerization (Docker) and deployment pipelines,

• experience with cloud-native ML platforms, preferably Google Cloud / Vertex AI,

• solid understanding of: model evaluation beyond accuracy (fairness, robustness, monitoring) and  CI/CD for ML systems (MLOps practices),

• familiarity with artifact management and version control systems. 

🟣 Nice to have:

• experience building enterprise AI/ML platforms supporting multiple teams/products,

• knowledge of data governance, lineage, and compliance frameworks Exposure to high-scale ML systems and real-time inference architectures,

• experience implementing automated retraining and adaptive learning systems.

🟣 Recruitment Process:

CV review – HR call – Interview – Client Interview – Decision

🎁 Benefits 🎁

✍ Development:

• development budgets of up to 6,800 PLN,

• we fund certifications e.g.: AWS, Azure,

• access to Udemy, O'Reilly (formerly Safari Books Online) and more,

• events and technology conferences,

• technology Guilds,

• internal training,

• Xebia Upskill.

🩺 We take care of your health:

• private medical healthcare,

• multiSport card - we subsidise a MultiSport card,

• mental Health Support.

🤸‍♂️ We are flexible:

• B2B or employment contract,

• contract for an indefinite period.