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Mayflower is a technology company that alters the entertainment industry to a new level of perception and engagement.
We are looking for a Lead Machine Learning Engineer 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.
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
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.)
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.
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