Senior Principal Machine Learning Engineer

Job Description

About the Role

Title: Sr Principal Machine Learning Engineer Job Details | PubMatic, Inc.

Location:

Redwood City, CA, US

Department: Machine Learning/Ad Serving

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.

Position Description

We are immediately hiring a Sr Principal Machine Learning Engineer 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