# Engineering Manager – AI Engineering

**Company**: Meesho
**Location**: Bangalore, Karnataka
**Work arrangement**: onsite
**Experience**: senior
**Job type**: Full Time Employee
**Category**: Engineering
**Industry**: Technology

**Apply**: https://jobs.lever.co/meesho/a1cc7ad9-a233-4ba6-b53b-e56116f6ac27?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_8a610b63-509

## Description

## About the Role

We are looking for an experienced Engineering Manager – AI Engineering to lead the development of scalable AI platforms and infrastructure while managing high-performing engineering teams. You will drive the design, delivery, and optimization of production-grade AI systems powering AI use cases across Meesho.

## Responsibilities

- Lead, mentor, and grow a team of AI engineers , setting technical direction, raising the engineering bar, and owning execution and delivery end to end.

- Architect and scale Meesho's AI platform: cross-region model inference, multi-GPU fleet allocation and management, distributed training, and feature-engineering infrastructure.

- Drive inference optimization across the full stack , GPU kernel tuning, quantization (including outlier/tail-distribution handling), and memory/IO-bandwidth optimization , while building agents that codify and delegate known optimization procedures.

- Optimize open-weight models at both the model and inference-engine level , distillation, quantization, speculative decoding, KV-cache and serving-engine tuning.

- Scale data-science productivity through autonomous, agent-driven workflows spanning feature engineering, model training, and rollout.

- Push the frontier across MLOps, LLMOps, compute efficiency, and distributed ML systems.

- Partner with Product, Data Science, and Platform teams to turn AI capabilities into production impact for millions of users.

- Own the team's operating rhythm: hiring, performance management, sprint planning, and OKRs.

## Requirements

- Bachelor's or Master's in Computer Science or a related field.

- 9+ years of software engineering experience, including 2+ years managing engineers.

- Strong hands-on experience with the modern LLM inference stack , TensorRT-LLM, vLLM, SGLang , and with production, low-latency model serving at scale.

- Depth in inference optimization: GPU kernel tuning, quantization, speculative decoding, KV-cache and memory/IO optimization. CUDA / GPU programming experience is a strong plus.

- Experience with distributed training and the frameworks behind it , PyTorch FSDP, DeepSpeed, Megatron, or Ray.

- Experience running GPU fleets in production , Kubernetes (ideally GKE), GPU scheduling and allocation, and multi-region/multi-cluster deployment.

- Familiarity with building LLM-powered agents and agentic workflows, and a point of view on where autonomy can replace manual engineering toil.

- Experience with big-data and streaming stacks , Spark, Flink, or similar.

- Proficiency in Python; systems-level fluency (C++ / Go / Rust) for performance-critical paths.

- Strong leadership, problem-solving, and stakeholder-management skills.

## Preferred

- Open-source contributions to inference engines, training frameworks, or ML infra tooling.

- Experience managing GPU cost/efficiency (FinOps) for a large fleet on Cloud and Neo-Clouds.

- Track record building platforms for high-scale consumer products (millions of users).

- Familiarity with observability and reliability for ML systems (SLOs, autoscaling, incident response).

## Skills

### Required
- Python
- C++
- Go
- Rust
- TensorRT-LLM
- vLLM
- SGLang
- PyTorch FSDP
- DeepSpeed
- Megatron
- Ray
- Kubernetes
- GPU programming
- Distributed training
- LLM inference stack
- Inference optimization
- Big-data and streaming stacks

### Nice to have
- Open-source contributions
- GPU cost/efficiency management
- Building platforms for high-scale consumer products
- Observability and reliability for ML systems

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Source: [Apply at jobs.lever.co](https://jobs.lever.co/meesho/a1cc7ad9-a233-4ba6-b53b-e56116f6ac27?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)