ML Engineer: Scale Ad AI & Open-Source LLMs

InMobi Advertising; San Mateo (CA); On-site; USD 173,000 - 210,000; Full time

Benefits offered by this job

RSU grant

Medical, dental, vision insurance

401(k)

Generous vacation

Maternity/paternity leave

Flexible working hours

Wellness stipend

Free lunch

Pet-friendly office

Employee Assistance Program

Job summary

InMobi Advertising is seeking a Machine Learning Engineer to develop and optimize ad science models, open-source LLMs, and supporting infrastructure. You’ll work on high‑impact problems like creative optimization, personalization, targeting, and compute scaling across GPUs/TPUs.

You will join experienced researchers and engineers, shaping the infrastructure and models behind ad intelligence at massive scale, with close collaboration across data and platform teams.

Qualifications

• Master’s degree in machine learning or a related field; PhD is a plus.
• At least 3 years of experience as a Machine Learning Engineer building large‑scale ML systems.
• Expertise in Python; familiarity with Java is a plus.
• Experience with PyTorch and accelerator-based inference systems.

Responsibilities

• Build and support training pipelines and model implementations.
• Adapt OpenRLHF and DeepSpeed for post-training needs.
• Optimize online and batch inference for low latency and cost.
• Build monitoring and evaluation solutions for reliability.
• Leverage data features to strengthen pipelines for training and inference.
• Explore platforms like JAX on TPUs to diversify compute.
• Collaborate with Applied Scientists on experiment design and modeling.

Skills

Python

PyTorch

Distributed systems

Reinforcement learning

Education

Master's degree in ML or related field

PhD a plus

Tools

Kubernetes

Airflow

Spark

DeepSpeed

OpenRLHF

Triton

ONNX

TensorRT

Job description

InMobi Advertising is seeking a Machine Learning Engineer to develop and optimize ad science models, open-source LLMs, and supporting infrastructure. You’ll work on high‑impact problems like creative optimization, personalization, targeting, and compute scaling across GPUs/TPUs.

You will join experienced researchers and engineers, shaping the infrastructure and models behind ad intelligence at massive scale, with close collaboration across data and platform teams.