On-site opportunity at
MeeshoEngineering Manager – AI Engineering
The Engineering Manager, AI Engineering role leads the team that builds and scales Meesho's AI platform. The posting says the platform answers more than one million…
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About This Role
The Engineering Manager, AI Engineering role leads the team that builds and scales Meesho's AI platform. The posting says the platform answers more than one million deep-learning model requests a second on ordinary days, with volume rising more than threefold on sale days. It underpins image matching, fraud detection, logistics, ranking, recommendations and search. The job is based in Bengaluru. The manager leads AI engineers, sets technical direction and owns…
Job Description
The Engineering Manager, AI Engineering role leads the team that builds and scales Meesho's AI platform. The posting says the platform answers more than one million deep-learning model requests a second on ordinary days, with volume rising more than threefold on sale days. It underpins image matching, fraud detection, logistics, ranking, recommendations and search. The job is based in Bengaluru.
The manager leads AI engineers, sets technical direction and owns delivery from start to finish. The platform work spans inference served across regions, GPU capacity planning across fleets, distributed training and feature tooling. The role also covers inference optimisation at the kernel, quantisation and memory levels, and tuning open-weight models through distillation and serving-engine work.
Other areas include building agent-driven workflows that make data science work more productive, pushing forward MLOps and LLMOps practice, and coordinating with the product, data science and platform groups. The manager oversees hiring, people reviews, sprint cadence and OKR tracking.
It suits a senior engineer with at least nine years of software experience, including two or more years managing engineers, who has deep production experience with LLM serving stacks, GPU infrastructure and distributed machine learning.
Responsibilities
- Mentor AI engineers, set technical direction and own delivery end to end.
- Design and scale the AI platform, including cross-region inference, GPU fleet management, distributed training and feature infrastructure.
- Drive inference optimisation across GPU kernels, quantisation and memory and IO bandwidth.
- Tune open-weight models across both modelling and inference-engine layers.
- Build agent-driven workflows that automate parts of feature engineering, training and rollout.
- Advance MLOps and LLMOps practice, plus compute efficiency and distributed machine learning.
- Work alongside product, data science and platform colleagues to bring AI capabilities into production for large user numbers.
Requirements
- A degree in computing or a closely related field, at bachelor's or master's level.
- At least nine years in software engineering, two or more of them spent managing engineers.
- Hands-on experience with a modern LLM inference stack and low-latency production model serving at scale.
- Depth in inference optimisation, including GPU kernel tuning, quantisation, speculative decoding and KV-cache work.
- Hands-on use of distributed training libraries such as Ray, DeepSpeed, Megatron or PyTorch FSDP.
- Hands-on work operating GPU clusters on Kubernetes across several regions.
- Familiarity with Spark, Flink or comparable data-streaming tooling.
- Proficiency in Python, with systems-level skills in C++, Go or Rust for performance-critical paths.
- Good leadership, analytical and stakeholder-handling ability.
Qualifications
- Working knowledge of CUDA or GPU kernels would stand out.
- Public open-source work on serving engines, training libraries or ML infrastructure tooling.
- Experience keeping GPU spending and utilisation under control for a big fleet across cloud and neo-cloud providers.
- Prior success creating systems that serve large consumer audiences.
- Comfort with monitoring and dependability of ML systems, covering SLOs, autoscaling and incident handling.
Core Skills
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Where is the role based?
The role is listed as on-site in Bengaluru.
What experience is required?
The posting asks for at least nine years in software engineering, two or more of them spent managing engineers.
What technical areas does the role cover?
The posting covers LLM inference, GPU fleet management, distributed training, MLOps and LLMOps, and inference optimisation.
What is the salary?
The posting does not specify a salary.
How do I apply?
The posting does not describe an application process.
Sample Interview Questions
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