Design, build, and maintain scalable ML pipelines on GCP using Python, BigQuery/Spark, Kubernetes, and CI/CD best practices
Job Summary
Design, build, and maintain scalable ML pipelines on GCP using Python, BigQuery/Spark, Kubernetes, and CI/CD best practices.
Mentor & grow a small team—provide technical guidance, establish code-review norms, and cultivate a culture of rapid, well-engineered experimentation.
Collaborate cross-functionally with plant scientists, data engineers, and the automation group to ingest high-throughput phenotyping data and close feedback loops.
Matching Summary
Design, build, and maintain scalable ML pipelines on GCP using Python, BigQuery/Spark, Kubernetes, and CI/CD best practices.
Salary
$170,000 - $220,000 per year
Skills & Requirements
Must-have
Scalable ML pipelines on GCP
Python, BigQuery/Spark, Kubernetes
Model-ops lifecycle ownership
Cross-functional collaboration
MLOps Excellence infrastructure
Nice-to-have
Foundation Models and Self-Supervised Learning
Key Requirements
5+ years building production ML/AI systems
Technical lead experience preferred
Expert Python plus one ML framework (JAX/NumPyro, TensorFlow, or PyTorch)