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Staff Engineer, Machine Learning (Senior)

PubMatic
Redwood City, United Statesfull_timeVerifiedPosted 1 Aug 2023
💰 $260,000/yr($230,000/yr$260,000/yr)

About the role

Company Description

PubMatic (Nasdaq: PUBM) delivers superior revenue to publishers by being an SSP of choice for agencies and advertisers.

PubMatic’s cloud infrastructure platform for digital advertising empowers app developers and publishers to increase monetization while enabling media buyers to drive return on investment by reaching and engaging their target audiences in brand-safe, premium environments across ad formats and devices.

Since 2006, PubMatic has been expanding its owned and operated global infrastructure and continues to cultivate programmatic innovation. PubMatic operates 14 offices and eight data centers worldwide.

Job Description

We are immediately hiring a Staff Engineer, Machine Learning to join our growing team in Redwood City on a hybrid schedule.

Reporting to the SVP of Addressability & Marketplace in Eastern Time, this senior contributor is a proven 'doer' to develop, implement and extend data-intensive ML software for real-time auctioning, ad inventory estimation, and audience segmentations. Working with our Big Data, Ad Serving, and Product Managers, you will apply Machine Learning to create POCs (Proofs of Concept). Then you will lead other Data Scientists to implement the POCs into production and scale up the solutions.

Responsibilities:

  • Design and implement core components of our algorithms, as well as model the large amounts of data that PubMatic generates daily
  • Develop and implement data-intensive machine learning software for real-time auctioning, ad inventory estimation, audience segmentations, and other AdTech applications
  • Work with data scientists, product managers, and software engineers to develop and support the software for new Machine Learning products
  • Ensure excellence in delivery to internal and external customers

Qualifications

  • PhD in a STEM field required
  • 3+ years of hands-on industry work experience designing and building large-scale ML algorithms and ETL that are well-designed, cleanly coded, well-documented, operationally stable, and timely delivered
  • 5+ years total analytical work, including academic research

Solid Experience with a Mix of:

  • Python or R, including ML libraries (SKLearn, NumPy, caret, e1071), including CPU/GPU parallelization, matrix algebra, vectorization, linear programming, lambda programming, OOP
  • At least one of the DL frameworks (TensorFlow, PyTorch, Caffe, Theano, Keras, or alike)

Understanding of:

  • Graduate statistics and probability (inference, hypothesis testing, p-value, ANOVA, CLT, LLN, Bayes’ theorem, A/B testing, combinatorics, PDF/CDF, joint/conditional/marginal densities)
  • Vector calculus (gradients, Jacobians, partial derivatives and integrals, optimization)
  • Linear algebra (eigen values/vectors, inverses, decompositions, orthogonality, multi-linear)
  • Time series (ARIMA, GARCH, forecasting, Kalman filter)
  • Shallow ML algorithms: regressions, SVM, kMeans, kNN, NB, HMM, PCA, NMF, SVD, XGBoost, decision trees, ensemble methods (random forest) 
  • Deep NN algorithms: MLP, RNN, LSTM, CNN, GRU
  • ML concepts: backprop, hyperparameter tuning (Bayesian optimization, grid/random search), regularization, learning rate, optimization
  • Advanced work with SQL or NoSQL, including nested/join/aggregate queries, stored procedures, over partition by, basic stat functions
  • Cloud compute engines (AWS, Azure, GCP and alike), ML on clusters of GPUs, SageMaker, Jupyter
  • Excellent communication skills, cultural fit and natural curiosity in learning the ML developments and domain expertise

Nice to Have:

  • Experience in Programmatic advertising and RTB
  • Deep reinforcement learning (Bellman equations, MDP, policy optimization, credit assignment, or multi-agent)
  • Proficiency with Spark (ML Lib, GraphX), Hadoop, Kafka, Hive
  • Scala, Java, C/C++
  • Record of STEM publications in top journals or conferences
  • High rank at Kaggle competitions

Compensation and Benefits:
Base Compensation Range: $230,000 - $260,000

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.

#LI-SD1

Additional Information

Return to Office: PubMatic employees around the world have returned to our offices

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PubMatic

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