ML Lead (Engineering)

TL;DR

ML Lead (Engineering) (ML/Backend): Building and delivering production-grade ML-powered applications with an accent on turning models into reliable, scalable, user-facing services. Focus on designing production ML services, integrating models into applications, ensuring reliability and performance under high load.

Location: Temporary remote (future relocation to Limassol)

Company

Technology company altering the entertainment industry to a new level of perception and engagement.

What you will do

• Design and build production ML services including APIs, microservices, and real-time systems
• Integrate ML models into user-facing applications
• Ensure reliability, scalability, and performance of ML-powered systems
• Define best practices for serving, versioning, and monitoring models in production
• Own the delivery pipeline of ML features into production and lead architectural decisions for low-latency high-load systems
• Collaborate with ML engineers, data scientists, DevOps, and MLOps teams; mentor engineers

Requirements

• 5+ years in software engineering / ML engineering
• Strong experience building production backend systems (Python preferred)
• Hands-on experience deploying and serving ML models in production
• Experience with API development (FastAPI, Flask, gRPC, etc.)
• Understanding of system design, scalability, and high-load environments
• Experience with ML pipelines and model lifecycle; ability to bridge ML and engineering teams
• Experience in Lead or Senior role (mentoring, ownership, decision-making)

Nice to have

• Experience with real-time ML systems (recommendations, ranking, personalization)
• Experience in video streaming or high-throughput platforms
• Familiarity with Kubernetes and cloud/on-prem environments
• Experience with feature stores, model monitoring, A/B testing
• Experience with MLOps platforms (MLflow, Airflow, etc.)

Culture & Benefits

• Full remote work (temporary)
• Competitive compensation with service contract; transparent performance reviews twice a year with bonuses and adjustments
• Annual allowance for home office, sports, equipment
• Paid language courses, learning platforms, mindfulness and psychological support (50% coverage)
• Career growth in fast-scaling project with influence on technical decisions
• Peer reward program for team contributions