Staff Engineer, Machine Learning

at  PubMatic

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

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