Senior Machine Learning Staff Engineer, PubMatic

• 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

Desirable

• We are immediately hiring a Machine Learning Staff Engineer to join our growing team in New York on a hybrid schedule
• Reporting to the SVP of Addressability & Marketplace, 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
• 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