Mayflower logo
Mayflower

FunTech pioneering the live entertainment industry at massive scale — top-50 global site, 200K RPS, millions of users

ML Lead (Engineering)

Engineering ManagerEngineering ManagerFull TimeRemoteLeadTeam 501-1,000H1B SponsorCompany SiteLinkedIn

Location

Worldwide

Posted

22 days ago

Salary

0

Seniority

Lead

No structured requirement data.

Job Description

ML Lead (Engineering)

Mayflower

Role Description 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 Qualifications - 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) Requirements - 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.) Benefits - Full remote work - Competitive compensation with a service contract - Transparent performance reviews twice a year, with bonus opportunities and salary adjustments - An annual allowance for home office improvements, sports activities, equipment upgrades, and more - 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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