2 years ago
Santa Clara, CA, USASenior
Base Salary
$160k - $200k/yr
Responsibilities
- Design and develop scalable systems for ML model training, inference, deployment, and monitoring.
- Build and maintain data pipelines, model versioning systems, and experiment-tracking frameworks.
- Manage large-scale GPU clusters and implement distributed systems and storage solutions for ML workloads.
- Improve CI/CD workflows for ML models and infrastructure.
- Implement monitoring, logging, alerting, availability, and reliability improvements for the ML platform.
- Collaborate with ML researchers and engineers to identify bottlenecks and improve platform usability.
- Evaluate and integrate relevant tools and frameworks.
- Mentor junior engineers and contribute to technical excellence.
- Comply with Quality Management System requirements and drive quality and process improvements.
Requirements
- PhD or MS in Computer Science, Electrical Engineering, or a related field.
- PhD new graduates are eligible, or candidates with a master’s degree should have 3+ years of software engineering experience focused on ML infrastructure or distributed systems.
- Proficiency in Python, C++, and SQL.
- Strong understanding of containerization, orchestration, distributed ML workloads, and experiment-tracking tools.
- Experience deploying and managing resources across AWS, GCP, or on-premises environments.
- Proficiency in at least one deep learning framework, such as PyTorch, and data pipeline tools such as Apache Airflow or Prefect.
- Strong knowledge of distributed systems, databases, and storage solutions.
- Extensive software design and development skills.
- Strong communication, adaptability, and ability to contribute productively in a collaborative environment.
- Preferred experience includes CNNs, Transformer models, large-scale ML datasets, MLOps pipelines, Ray, autonomous vehicles, or robotics.
Benefits
- $160,000–$200,000 annual salary range.
- Cash and equity compensation is determined by position, location, qualifications, and experience.
- Professional development opportunities in an innovative and dynamic field.
- Catered free lunch, unlimited snacks, and beverages.
- Benefits package including a 401(k) plan.
Tech Stack
Categories
Data EngineeringML Engineering
