Senior Machine Learning Engineer

PubMatic (Nasdaq: PUBM) is an independent technology company maximizing customer value by delivering digital advertising’s supply chain of the future.

PubMatic’s sell-side platform empowers the world’s leading digital content creators across the open internet to control access to their inventory and increase monetization by enabling marketers to drive return on investment and reach addressable audiences across ad formats and devices.

Since 2006, our infrastructure-driven approach has allowed for the efficient processing and utilization of data in real time. By delivering scalable and flexible programmatic innovation, we improve outcomes for our customers while championing a vibrant and transparent digital advertising supply chain.

Job Description
 

We are immediately hiring a results-oriented Senior Machine Learning Engineer to join our growing team in Redwood City on a hybrid schedule.

Reporting to the Director of Machine Learning, you will partner with Product and Engineering teams to both solve problems and identify new opportunities for the business.

The ideal candidate will apply quantitative analysis, modeling and data mining to help drive informed product decisions for PubMatic + get things done.

Responsibilities

• Perform deep dive analysis to understand and optimize the key product KPIs
• Apply statistics, modeling, and machine learning to improve the efficiency of systems and relevance algorithms across our business application products
• Conduct data analysis to make product recommendations and design A/B experiments
• Partner with Product and Engineering teams to solve problems and identify trends and opportunities
• Collaborate with cross-functional stakeholders to understand their business needs, formulate and complete end-to-end analysis that includes data gathering, analysis, ongoing scaled deliverables and presentations

Qualifications

• Quantitative BS or MS degree (e.g., Physics, Statistics, Mathematics, Economics, or Computer Science)
• 2+ years of hands-on experience designing Machine Learning models to solve business problems with statistical packages, such as R, MATLAB, Python (NumPy, Scikit-learn + Pandas) or MLlib
• Experience with articulating product questions and using statistics to arrive at an answer
• Experience with scripting in SQL - extracting large data sets and design of ETL flows
• Work experience in an inter-disciplinary/cross-functional field
• Deep interest and aptitude in data, metrics, analysis, trends and applied knowledge of measurement, statistics and program evaluation
• Distinctive problem-solving skills and impeccable business judgment
• Capable of translating analysis results into business recommendations

Compensation and Benefits:

Base Salary Range: $145,000 - $195,000

In accordance with applicable law, the above salary range provided is PubMatic’s reasonable estimate of the base salary for this role. The actual amount may vary, based on non-discriminatory factors such as location, experience, knowledge, skills and abilities. In addition to salary PubMatic also offers a bonus, restricted stock units and a competitive benefits package.

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, paid leave programs, paid holidays, healthcare, dental and vision insurance, disability and life insurance, commuter benefits, physical and financial wellness programs, unlimited DTO in the US (that we actually require you to use!), reimbursement for mobile, and fully stocked pantries plus in-office catered lunches 5 days per week.

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