Staff Engineer, Machine Learning

Position 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) and 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
• People leadership of a team is available, if that interests you

Requirements:

• 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 Salary 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.

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