At PubMatic, data operates at unmatched scale.
You will collaborate closely with ML Engineers, Data Scientists, and Product stakeholders to accelerate experimentation, maximize efficiency, and translate AI solutions from concept to production.
Design and maintain scalable ML pipelines for ingestion, training, evaluation, inference and deployment
Build large-scale data workflows on Spark, Hadoop, Kafka and Snowflake
Develop experiment tracking, automated reporting and model health monitoring
Provide reusable ML components, SDKs and APIs for other teams
Drive CI/CD, workflow orchestration and infrastructure-as-code for ML jobs
At PubMatic, data operates at unmatched scale. As a Senior Machine Learning Platform Engineer, you will design and scale the infrastructure and frameworks that enable machine learning development, experimentation, and production across a global ecosystem handling trillions of ad impressions.
You will collaborate closely with ML Engineers, Data Scientists, and Product stakeholders to accelerate experimentation, maximize efficiency, and translate AI solutions from concept to production. This role offers direct exposure to petabyte-scale datasets, industry-standard ML efficiency tools (e.g., Triton inference, GPU/accelerated computing), and the opportunity to evaluate and adopt emerging AI/ML technologies.
Design and maintain scalable ML pipelines and platforms for ingestion, feature engineering, training, evaluation, inference, and deployment.
Build and optimize large-scale data workflows using distributed systems (Spark, Hadoop, Kafka, Snowflake)
Develop frameworks for experiment tracking, automated reporting, and observability to monitor model health, drift, and anomalies.
Provide reusable components, SDKs, and APIs that empower teams to leverage AI insights and ML models effectively.
Drive CI/CD, workflow orchestration, and infrastructure-as-code practices for ML jobs, ensuring reliability and reproducibility.
Qualifications - Should have a bachelor’s degree in engineering (CS / IT) or equivalent degree from well-known Institutes / Universities. Additional Information:
PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes.
In the employer’s words · Read in context
Open 6 monthsWe first saw this posting 180 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 180
Up longer than most. Similar jobs usually come down between day 8 and day 76.
Well past Pubmatic’s usual: its jobs come down by about day 68.
From 5,460 similar postings that came down, and 8 of Pubmatic’s. Coming down is not always a hire.
7 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- ML Ops/Infrastructure: Experience with CI/CD, Docker, Kubernetes, Airflow/MLflow, and experiment tracking tools. - Programming: Skilled in Python/Scala/Java for data-intensive applications. - Problem Solving: Strong analytical skills and ability to debug complex data/ML pipeline issues.
- Four plus years of hands-on experience with petabyte-scale datasets and distributed systems. - Data Analytics: Proficiency in SQL, Python (pandas, NumPy), and analytics/BI tools for data exploration and monitoring. - Exposure to graph-based systems (Neo4j), RAG approaches, or embedding platforms.
- Big Data: Strong expertise with Spark, Hadoop, Kafka, and data warehousing (Snowflake, SparkSQL). - ML Ops/Infrastructure: Experience with CI/CD, Docker, Kubernetes, Airflow/MLflow, and experiment tracking tools. - Programming: Skilled in Python/Scala/Java for data-intensive applications.
- Experience building recommendation systems, personalization pipelines, or anomaly detection frameworks. - Familiarity with BI tools such as Looker or Grafana. - A passion for applied AI/ML and eagerness to bring research ideas into production.
- Platform Development: Design and maintain scalable ML pipelines and platforms for ingestion, feature engineering, training, evaluation, inference, and deployment. - Big Data & Analytics: Build and optimize large-scale data workflows using distributed systems (Spark, Hadoop, Kafka, Snowflake) to support analytics and model training. - Experimentation & Observability: Develop frameworks for experiment tracking, automated reporting, and observability to monitor model health, drift, and anomalies.
- A passion for applied AI/ML and eagerness to bring research ideas into production. - Big Data: Strong expertise with Spark, Hadoop, Kafka, and data warehousing (Snowflake, SparkSQL). - ML Ops/Infrastructure: Experience with CI/CD, Docker, Kubernetes, Airflow/MLflow, and experiment tracking tools.
- Data Analytics: Proficiency in SQL, Python (pandas, NumPy), and analytics/BI tools for data exploration and monitoring. - Exposure to graph-based systems (Neo4j), RAG approaches, or embedding platforms. - Experience building recommendation systems, personalization pipelines, or anomaly detection frameworks.
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New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
About the Role
At PubMatic, data operates at unmatched scale. As a Senior Machine Learning Platform Engineer, you will design and scale the infrastructure and frameworks that enable machine learning development, experimentation, and production across a global ecosystem handling trillions of ad impressions.
You will collaborate closely with ML Engineers, Data Scientists, and Product stakeholders to accelerate experimentation, maximize efficiency, and translate AI solutions from concept to production. This role offers direct exposure to petabyte-scale datasets, industry-standard ML efficiency tools (e.g., Triton inference, GPU/accelerated computing), and the opportunity to evaluate and adopt emerging AI/ML technologies.
You will contribute to the next-generation ML platform for adtech, enabling advanced use cases such as troubleshooting issues in bid stream, competitive intelligence, benchmarking, forecasting, reinforcement learning, and retrieval-augmented generation (RAG), while also establishing foundational capabilities like embeddings and observability frameworks.
What You’ll Do
We’d Love for You to Have
Qualifications
Additional Information:
Return to Office: PubMatic employees throughout the globe have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions.
Benefits: Our benefits package includes the best of what leading organizations provide, such as paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more!.
Diversity and Inclusion: PubMatic is proud to be an equal opportunity employer; we don’t just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status
About PubMatic
PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes.
Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.
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Pune, IN
Additional Information: Return to Office: PubMatic employees throughout the globe have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions. Benefits: Our benefits package includes the best of what leading organizations provide, such as paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more!.
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