Core & ML Ops Team Lead

Jobgether • India

Remote

This Job is No Longer Active This position is no longer accepting applications

AI Summary

Lead a cross-functional team in designing platforms for model training, orchestration, deployment, and monitoring. Ensure high performance, reliability, and security. Collaborate with product, operations, and security teams.

Key Highlights

Lead the Core & MLOps team

Design and maintain scalable infrastructure for model training, serving, and monitoring

Collaborate with product, operations, and security teams

Key Responsibilities

Lead the Core & MLOps team, overseeing roadmap, prioritization, delivery, and mentoring

Design, develop, and maintain scalable infrastructure for model training, serving, and monitoring

Build and maintain the Golden Path: reference repositories, scaffold CLIs, CI/CD pipelines, runtime contracts, and production-ready defaults

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Technical Skills Required

Linux/OS internals Networking Concurrency Performance profiling Kubernetes GPU infrastructure management Java Rust Go C++ Python CI/CD SRE practices Observability Reliability enablement

Benefits & Perks

Flexible remote work environment

Exposure to cutting-edge open-source technologies and ML infrastructure

Collaborative, multi-cultural team fostering innovation and knowledge sharing

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Nice to Have

Experience with streaming/workflow tools (Kafka, Argo, Temporal, Airflow)

Hands-on work with eBPF observability, perf tooling, or io_uring

Expertise in ML/AI cost optimization, multi-tenant quotas, and fairness

Job Description

This role is ideal for an experienced technical leader in MLOps and distributed systems, responsible for building and maintaining the scalable infrastructure that supports mission-critical services. You will lead a cross-functional team in designing platforms for model training, orchestration, deployment, and monitoring while ensuring high performance, reliability, and security. The position combines hands-on engineering with strategic team leadership, driving adoption of best practices, automation, and observability across the organization. You will collaborate with product, operations, and security teams to implement robust platforms that empower engineers to build and deploy services confidently. Mentorship, knowledge sharing, and establishing production-ready standards are central to your impact. This role allows you to shape platform strategy while staying deeply engaged in cutting-edge technologies and ML operations at scale.

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