14 of 14 Permanent Apache Beam Jobs

Sub Advanced capabilities in Python and SQL programming Track record of designing and refining ETL/ELT workflows Comprehensive knowledge of data modeling principles and warehouse design Familiarity with Apache Airflow and/or Apache Beam preferred Primary Duties: Design and deploy robust, scalable data pipeline architectures using GCP Create optimized ETL workflows to enable analytics and More ❯

for software systems Collaborate across teams to share knowledge and leading practices The team will work with technologies including: Open source, Commercial, and Government software packages such as Kafka, Beam, NumPy, Kubeflow, Nvidia Triton, PyTorch, TensorFlow, Weaviate, Neo4j, Grafana, etc. Cloud native techniques and containerization with Docker Infrastructure as Code with Terraform Leverage GitOps patterns and CI/CD More ❯

for data analysis purposes. Experience with common DBMS (PostgreSQL, MySQL, MongoDB etc.). Experience with data warehousing and parquet data manipulation (e.g. Athena, Redshift, BigQuery). Experience with Spark, Beam, Kafka, Hadoop or other data processing tools. Fluency in Python and experience on production-quality software development. Solid software engineering principles (software design patterns, configuration management, source control, build More ❯

make personalization smarter, faster, and more impactful. OUTCOMES Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale Enhance data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements Design ranking algorithms that balance relevance, diversity, and revenue Deliver real-time personalization with latency Run statistically rigorous A/B tests to More ❯

make personalization smarter, faster, and more impactful. OUTCOMES Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale Enhance data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements Design ranking algorithms that balance relevance, diversity, and revenue Deliver real-time personalization with latency Run statistically rigorous A/B tests to More ❯

make personalization smarter, faster, and more impactful. OUTCOMES Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale Enhance data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements Design ranking algorithms that balance relevance, diversity, and revenue Deliver real-time personalization with latency Run statistically rigorous A/B tests to More ❯

make personalization smarter, faster, and more impactful. OUTCOMES Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale Enhance data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements Design ranking algorithms that balance relevance, diversity, and revenue Deliver real-time personalization with latency Run statistically rigorous A/B tests to More ❯

make personalization smarter, faster, and more impactful. OUTCOMES Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale Enhance data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements Design ranking algorithms that balance relevance, diversity, and revenue Deliver real-time personalization with latency Run statistically rigorous A/B tests to More ❯

make personalization smarter, faster, and more impactful. OUTCOMES Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale Enhance data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements Design ranking algorithms that balance relevance, diversity, and revenue Deliver real-time personalization with latency Run statistically rigorous A/B tests to More ❯

make personalization smarter, faster, and more impactful. OUTCOMES Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale Enhance data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements Design ranking algorithms that balance relevance, diversity, and revenue Deliver real-time personalization with latency Run statistically rigorous A/B tests to More ❯

make personalization smarter, faster, and more impactful. OUTCOMES Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale Enhance data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements Design ranking algorithms that balance relevance, diversity, and revenue Deliver real-time personalization with latency Run statistically rigorous A/B tests to More ❯

make personalization smarter, faster, and more impactful. OUTCOMES Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale Enhance data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements Design ranking algorithms that balance relevance, diversity, and revenue Deliver real-time personalization with latency Run statistically rigorous A/B tests to More ❯

make personalization smarter, faster, and more impactful. OUTCOMES Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale Enhance data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements Design ranking algorithms that balance relevance, diversity, and revenue Deliver real-time personalization with latency Run statistically rigorous A/B tests to More ❯

the-art machine learning models using Tensorflow for real-world, large-scale problems. Construct and maintain data pipelines for model training and serving using Google cloud products such as Apache Beam/Dataflow, BigQuery, and BigTable. Develop highly scalable model servers on cloud platforms. Work with product, account, and infrastructure engineering teams to define future product roadmaps. Basic More ❯