Machine Learning Engineer

About the Role

Responsibilities

• Build and maintain robust ML infra (training, serving, monitoring).
• Deploy LLMs, RAG pipelines, and detectors into production at scale.
• Translate research prototypes into production-ready APIs/services.
• Manage CI/CD pipelines, observability, experiment tracking.
• Optimize for latency, cost, and reliability.
• Ensure security, compliance, and privacy in enterprise environments.
• Collaborate closely with ML researchers, back-end engineers, and product teams.

Requirements

• 4+ years as ML Engineer / MLOps / related role.
• Strong Python + ML frameworks (PyTorch/TensorFlow).
• Cloud platforms (AWS/GCP/Azure) + Kubernetes/Docker.
• Track record deploying ML models in production (REST/gRPC, FastAPI).
• CI/CD pipelines, monitoring, experiment tracking (MLflow, W&B).
• Understanding of enterprise security & compliance (SOC2, ISO 42001, EU AI Act).

• LLMs, RAG systems, or retrieval optimization.
• Experience with GPUs/distributed training.
• Work in regulated industries (finance, insurance, healthcare).
• Contributions to open-source ML tooling.

Why Join Alinia?

• Build AI safety infrastructure at the frontier of enterprise adoption.
• Work on applied ML with real-world impact.
• Competitive compensation + meaningful equity.
• Early, high-impact role in a mission-driven startup.