Job description

InMobi (Corporate) InMobi Group is a global technology company shaping the future of agentic commerce and advertising. Through its ecosystem of businesses — including InMobi Advertising and flagship consumer platform Glance — InMobi leverages data, machine learning, and generative AI to help brands reach audiences more precisely and consumers discover products more intuitively. Glance, which is pioneering new models of agentic commerce, is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd. InMobi Advertising InMobi Advertising, part of global technology company InMobi, is an agentic advertising platform helping brands and merchants achieve their business outcomes. Through its proprietary intelligence, AI-led solutions, and vast consumer reach — including flagship consumer platform Glance — InMobi Advertising delivers the omnichannel performance defining what's next in advertising and commerce. Glance is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd. To learn more, visit advertising.inmobi.com. Glance Glance is an intelligent shopping agent, redefining the commerce experience. Powered by proprietary agentic intelligence and generative AI, Glance delivers a hyper-personalized consumer experience across mobile and TV — shaping the new era of shopping. Glance is operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of global technology leader InMobi, and is backed by Mithril Capital, Google and Jio Platforms. To learn more, visit glance.com. Overview of the Role: We are looking for a Machine Learning Engineer to develop and optimize our ad science models, open-source LLMs, and the underlying infrastructure that powers them — with a constant eye toward performance and cost. AI and ML sit at the core of InMobi's business, and our science teams are tackling some of the field's most interesting problems: creative optimization, user personalization, targeting, yield management, traffic shaping, and more. We're moving fast and deep into architectural research, generative AI adoption, compute scaling on the latest accelerators (GPUs/TPUs), and advances in reinforcement learning. You'll join a team of experienced researchers and engineers who have been pushing the boundaries of ad science research for over a decade, working closely with data and platform engineering to build solutions that scale and serve the needs of every science team across the organization. This is a chance to shape the infrastructure and models behind ad intelligence operating at truly massive scale. The Impact You'll Make: Build and support training pipelines and model implementations that maximize experimentation velocity Adapt open-source LLM infrastructure like DeepSpeed and OpenRLHF to meet InMobi-specific post-training needs Optimize online and batch inference for low latency and cost efficiency Build monitoring and evaluation solutions that keep our infrastructure reliable and our models behaving as expected Leverage the breadth of data features across our product portfolio to strengthen our data pipelines and unlock new features for training and inference Explore new platforms and ecosystems (e.g., JAX on TPUs) to help diversify our compute Collaborate closely with Applied Scientists on active research, contributing directly to experiment design and modeling The Experience We Need: Master's degree in machine learning or a related field required; a PhD is a plus At least 3 years of experience as a Machine Learning Engineer, building state-of-the-art machine learning/deep learning systems at extreme scale Expertise in large-scale distributed data systems, including high-performance relational and key-value stores, orchestrators like Airflow, and data transformations in Spark Expertise in Python; familiarity with Java (especially in high-performance serving systems) is a plus Expertise in PyTorch or a similar ecosystem Experience with accelerator-based inference systems such as Triton, and optimization backends like ONNX and TensorRT Experience with cloud platforms and container orchestration using Kubernetes Knowledge of deep recommender systems, including two-tower and attention-based architectures, is a plus Knowledge of reinforcement learning systems — including RL approaches, reward signals, and post-training feedback loops — is a plus Understanding of the ads ecosystem (OpenRTB, SSPs, DSPs, ad exchanges, MMPs) is a plus At InMobi, you’ll be surrounded by people who… Think big and act fast: We’re entrepreneurial, thrive in ambiguity, and love solving high-impact problems Are passionate, fanatically driven, and take immense pride in their work: We care deeply about the impact we create and continuously push our potential Own their outcomes: We take responsibility, make bold decisions, and execute with confidence Embrace freedom with accountability: We value autonomy and understand that trust comes with responsibility Believe in lifelong learning: We welcome feedback, challenge ourselves to grow, and aren’t afraid to take smart risks Award-winning culture, best-in-class benefits Our compensation philosophy enables us to provide a competitive salary that drives high performance while balancing business needs and pay parity. We determine compensation based on a wide variety of factors, including role, nature of experience, skills, and location. The base (fixed) salary for this role ranges from $172,500 to $210,000 USD (min to max of base salary pay range). This salary range applies to our offices in California and New York * . *Our ranges may vary based on the final location and region of the role in accordance with the geographical differentiation in pay scales in the country. In addition to cash compensation, based on the position, an InMobian can receive equity in the form of ESOPs (Employee Stock Option Plan). We believe that our employees/personnel should have the ability to own a part of the entity they are a part of. Therefore, the entity employing you may elect to provide such stock to you. Ownership of stock enables us to treat our employer company as our own and base our decisions on the company’s best interests. To encourage a spirit of shared ownership, we grant InMobians relevant company stock(s). As you contribute to the growth of your company, certain stocks may be issued to you in recognition of your contribution. A quick snapshot of our benefits: Competitive salary and ESOP grant (where applicable) High-quality medical, dental, and vision insurance (including company-matched HSA) 401(k) company match Generous combination of vacation time, sick days, special occasion time, and company-wide holidays Substantial maternity and paternity leave benefits and a compassionate work environment Flexible working hours to suit everyone Wellness stipend for a healthier you! Free lunch provided in our offices daily Pet-friendly work environment and robust pet insurance policy - because we love our animals! Employee Assistance Program (EAP) If this sounds like the kind of team, role, values, benefits, and challenges that excite you, we’d love to hear from you. Go for it! InMobi is an equal opportunity employer       InMobi is a place where everyone can grow. Howsoever you identify, and whatever background you bring with you, we invite you to apply if this sounds like a role that would make you excited to work.  InMobi provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type.  All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.  The InMobi Culture At InMobi, culture isn’t a buzzword; it's an ethos woven by every InMobian, reflecting our diverse backgrounds and experiences. We thrive on challenges and seize every opportunity for growth. Our core values — thinking big, being passionate, showing accountability, and taking ownership with freedom — guide us in every decision we make. We believe in nurturing and investing in your development through continuous learning and career progression with our InMobi Live Your Potential program. InMobi is proud to be an Equal Employment Opportunity employer and is committed to providing reasonable accommodations to qualified individuals with disabilities throughout the hiring process and in the workplace. Visit inmobi.com to better understand our benefits, values, and more!

Requirements

Must-haves

InMobi (Corporate)
InMobi Advertising
We are looking for a Machine Learning Engineer to develop and optimize our ad science models, open-source LLMs, and the underlying infrastructure that powers them — with a constant eye toward performance and cost.
Build and support training pipelines and model implementations that maximize experimentation velocity
Adapt open-source LLM infrastructure like DeepSpeed and OpenRLHF to meet InMobi-specific post-training needs
Optimize online and batch inference for low latency and cost efficiency
Build monitoring and evaluation solutions that keep our infrastructure reliable and our models behaving as expected
Leverage the breadth of data features across our product portfolio to strengthen our data pipelines and unlock new features for training and inference
Explore new platforms and ecosystems (e.g., JAX on TPUs) to help diversify our compute
Collaborate closely with Applied Scientists on active research, contributing directly to experiment design and modeling
At least 3 years of experience as a Machine Learning Engineer, building state-of-the-art machine learning/deep learning systems at extreme scale
Expertise in large-scale distributed data systems, including high-performance relational and key-value stores, orchestrators like Airflow, and data transformations in Spark
Expertise in PyTorch or a similar ecosystem
Experience with accelerator-based inference systems such as Triton, and optimization backends like ONNX and TensorRT
Experience with cloud platforms and container orchestration using Kubernetes
At InMobi, you’ll be surrounded by people who…
Think big and act fast: We’re entrepreneurial, thrive in ambiguity, and love solving high-impact problems
Are passionate, fanatically driven, and take immense pride in their work: We care deeply about the impact we create and continuously push our potential
Own their outcomes: We take responsibility, make bold decisions, and execute with confidence

Nice-to-haves

Master's degree in machine learning or a related field required; a PhD is a plus
Expertise in Python; familiarity with Java (especially in high-performance serving systems) is a plus
Knowledge of deep recommender systems, including two-tower and attention-based architectures, is a plus
Knowledge of reinforcement learning systems — including RL approaches, reward signals, and post-training feedback loops — is a plus
Understanding of the ads ecosystem (OpenRTB, SSPs, DSPs, ad exchanges, MMPs) is a plus

Application prep

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Keywords to mirror

machine learningaimlllmpythonjavakubernetesgo

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Wellness