ML Lead (Engineering)

Mayflower is a technology company that alters the entertainment industry to a new level of perception and engagement.

We are looking for a Machine Learning Lead (Engineering) focused on building and delivering production-grade ML-powered applications.

This role is not about research or experimentation. You will be responsible for turning ML models into reliable, scalable, user-facing services.

You will work at the intersection of machine learning and backend engineering, owning the full lifecycle of ML-powered features — from integration to deployment and operation in production.

Job Responsibilities

• Design and build production ML services (APIs, microservices, real-time systems)

• Integrate ML models into user-facing applications

• Ensure reliability, scalability, and performance of ML-powered systems

• Define and implement best practices for serving, versioning, and monitoring models in production

• Collaborate closely with:

  • ML engineers / data scientists (who develop models)

  • DevOps / MLOps team (who provide platform and infrastructure)

• Own the delivery pipeline of ML features into production

• Lead and mentor engineers working on ML-powered applications

• Drive architectural decisions around low-latency and high-load systems

• Identify bottlenecks between experimentation and production and eliminate them

You’ll thrive here if you have

• 5+ years of experience 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 working with ML pipelines and model lifecycle

• Ability to bridge the gap between ML and engineering teams

• Experience in a Lead or Senior role (mentoring, ownership, decision-making)

  
  That can be a plus:

• 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 working alongside MLOps platforms (MLflow, Airflow, etc.)
  

  Conditions

  We know that great talent deserves great conditions, so here's what you can expect when joining us:

  • Full remote work;

  • Competitive compensation with a service contract;

  • Transparent performance reviews twice a year, with bonus opportunities and salary adjustments;

  • An annual allowance that you can use for home office improvements, sports activities, equipment upgrades, and more—tailor it to what benefits you most;

  • Investment in your development: paid language courses, access to various learning platforms, and a mindfulness benefit, including psychological support with 50% coverage;

  • Career growth in a fast-scaling project with opportunities to influence technical decisions;

  • A culture of recognition: our peer reward program celebrates contributions from across the team.