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InMobiMachine Learning Engineer – Ad Sciences
InMobi is hiring a Machine Learning Engineer for its Ad Sciences group. The role is full-time, and the posting does not name a work location. The…
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About This Role
InMobi is hiring a Machine Learning Engineer for its Ad Sciences group. The role is full-time, and the posting does not name a work location. The job centers on developing and optimizing ad science models and open-source large language models, along with the infrastructure that runs them, with constant attention to performance and cost. The science teams work on areas such as creative tuning, personalization for users, audience targeting, yield…
Job Description
InMobi is hiring a Machine Learning Engineer for its Ad Sciences group. The role is full-time, and the posting does not name a work location. The job centers on developing and optimizing ad science models and open-source large language models, along with the infrastructure that runs them, with constant attention to performance and cost.
The science teams work on areas such as creative tuning, personalization for users, audience targeting, yield control and shaping traffic flow. The company is moving into architectural research, generative AI, large-scale compute on GPUs and TPUs, and reinforcement learning. The engineer creates and keeps running training workflows and model code, adapts LLM training tools for InMobi-specific post-training needs, and tunes real-time and offline inference for speed and spend. Monitoring and evaluation systems are part of the scope, along with pipelines that use the wide range of data features across the product portfolio.
The engineer also explores new platforms, such as JAX on TPUs, to diversify compute options, and works alongside applied scientists on active research, including experiment design and modeling. The work targets ad intelligence systems that run at very large scale, and the research group has been working on ad science for more than a decade.
A master's in ML or an adjacent discipline is required, with a PhD considered a plus. The posting asks for at least 3 years as a machine learning engineer on large-scale deep learning systems, expertise in Python and PyTorch, and experience with distributed data systems, Airflow, Spark, Triton, ONNX or TensorRT, and Kubernetes. Knowledge of recommender systems, reinforcement learning and the advertising ecosystem is a plus.
Responsibilities
- Develop and maintain the training workflows and model code that let experiments move faster
- Adapt LLM training frameworks such as DeepSpeed and OpenRLHF for InMobi-specific post-training needs
- Tune real-time and offline inference for speed and spend
- Build monitoring and evaluation tools that keep infrastructure reliable and models on track
- Use data features across the product portfolio to strengthen training and inference pipelines
- Explore new compute ecosystems such as JAX on TPUs
- Work with applied scientists on experiment design and modeling
Requirements
- Master's-level education in ML or an adjacent discipline
- At least 3 years as a machine learning engineer on large-scale ML or deep learning systems
- Expertise in Python and PyTorch or a similar framework
- Experience with large distributed data systems, Airflow and Spark
- Experience with inference systems such as Triton, plus ONNX and TensorRT
- Experience with cloud platforms and Kubernetes
Qualifications
- PhD in a relevant field
- Java, especially for high-performance serving systems
- Knowledge of deep recommender architectures such as two-tower and attention-based models
- Reinforcement learning, reward design and feedback loops after training
- Understanding of the ads ecosystem, including OpenRTB, SSPs, DSPs, ad exchanges and MMPs
Core Skills
Benefits
- Base pay plus an RSU grant where the role qualifies
- Medical, dental and vision coverage, including an employer-matched HSA
- 401(k) with an employer match
- Paid vacation, sick leave, personal occasion time and company holidays
- Parental leave for maternity and paternity
- Flexible working hours
- Wellness stipend, daily lunch in the office and an employee assistance program
- Pet insurance and a pet-friendly office
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 posting does not list a city or office for this role.
What is the salary?
The posting gives a base range between $172,500 and $210,000 USD and says it applies to California and New York offices. Final pay may vary by location.
What experience is required?
A master's in ML or an adjacent field and at least 3 years as a machine learning engineer. A PhD is a plus.
Is equity offered?
Based on the position, equity may be offered as RSUs, plus additional stock that may be issued over time.
How do I apply?
The posting does not describe an application process.
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