Company Description|Job Description
PubMatic is a publisher-focused sell-side platform for an open digital media future. We exist to help our clients succeed. We work tirelessly to optimize your performance while our SSP enables you to make smart, strategic decisions.
Featuring leading omni-channel revenue automation technology for publishers & enterprise-grade programmatic tools for media buyers, PubMatic's publisher-first approach enables advertisers to access premium inventory at scale.
Processing over one trillion ad impressions per month, PubMatic has created a global infrastructure to drive publisher monetization & control over their ad inventory.
Since 2006, PubMatic's focus on data & technology innovation has fueled the rise of the programmatic industry as a whole. Headquartered in Redwood City, California, PubMatic operates 13 offices & six data centers worldwide.
We are immediately hiring a strong Data ScientistorMachine Learning Engineerto join us in Redwood City- a proven 'doer' to develop, implement & extend data-intensive machine learning software for real-time auctioning, ad inventory estimation, & audience segmentations.
You will design & implement core components of our algorithms, as well as model & monetize the large amounts of data that PubMatic generates daily.
Working with our Data Science & AdServing teams, you willapply Machine Learning to help get things done.
- Development & implementation of data-intensive machine learning software for real-time auctioning, ad inventory estimation, audience segmentations, & other AdTech applications
- Working with data scientists, product managers, & software engineers to develop & support the software for new Machine Learning products
- Ensuring excellence in delivery to internal & external customers
- MS / PhD in STEM field
3+ years of hands-on industry work experience designing & building large-scale ML algorithms & ETL that are well-designed, cleanly coded, well-documented, operationally stable, & timely delivered
5+ years total analytical work, including academic research
Solid Experience with a mix of the following:
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)
- Graduate statistics & 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 & 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 & alike), ML on clusters of GPUs, SageMaker, Jupyter
- Excellent communication skills, cultural fit & natural curiosity in learning the ML developments & domain expertise
Nice to have:
- Experience inProgrammatic advertising & RTB
- Deep reinforcement learning (Bellman equations, MDP, policy optimization, credit assignment, 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
PubMatic is proud to be an equal opportunity employer; we don't just value diversity, we promote & celebrate it.
We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
All your information will be kept confidential according to EEO guidelines.