Senior Machine Learning Infrastructure Engineer
Santa Clara, CA
Data Engineering – Machine Learning and Data Engineer /
Full-time /
Hybrid
Plus is a global provider of highly automated driving and fully autonomous driving solutions with headquarters in Silicon Valley, California. Named by Forbes as one of America’s Best Startup Employers and Fast Company as one of the World’s Most Innovative Companies, Plus’s open autonomy technology platform is already powering vehicles in commercial use today. Working with one of the largest companies in the U.S., vehicle manufacturers, and others globally, Plus is helping to make driving safer, more comfortable, and more sustainable. Plus has received a number of industry awards and distinctions for its transformative technology and business momentum from Fast Company, Forbes, Insider, Consumer Electronics Show, AUVSI, and others. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.
Responsibilities:
- Design and develop scalable, high-performance systems for training, inference, deploying, and monitoring ML models at scale.
- Build and maintain efficient data pipelines, model versioning systems, and experiment tracking frameworks.
- Collaborate with cross-functional teams, including ML researchers and engineers, to identify bottlenecks and improve platform usability.
- Implement distributed systems and storage solutions optimized for machine learning workloadsDrive improvements in CI/CD workflows for ML models and infrastructure.
- Ensure high availability and reliability of the ML platform by implementing robust monitoring, logging, and alerting systems.
- Stay current with industry trends and integrate relevant tools and frameworks to enhance the platform.
- Mentor junior engineers and contribute to a culture of technical excellence
Required Skills:
- MS in Computer Science, Electrical Engineering, or related field
- Good oral and written communication skills
- 3+ years of software engineering experience with a focus on ML infrastructure or distributed systems.
- Proficiency in in Python, C++, SQL
- Deep understanding of containerization, orchestration technologies, distributed ML workload, and experiment tracking tools (e.g., Docker, Kubernetes, multiprocessing, Kubeflow, and mlflow)
- Deploy and manage resources across multiple cloud platforms (AWS, GCP, or on-prem environments)
- Proficiency in at least one deep learning framework, such as PyTorch and data pipeline tools (e.g., Apache Airflow, Prefect).
- Strong knowledge of distributed systems, databases, and storage solutions.
- Extensive software design and development skills.
- Ability to learn and adapt to new technologies and contribute in a productive environment.
Preferred Skills:
- Familiarity with fundamental deep learning architectures, such as Convolutional Neural Networks (CNNs) and Transformer models
- Experience in building large-scale ML datasets, MLOps pipelines, and distributed computing frameworks like Ray
- Experience working with autonomous vehicles or robotics
Salary Range:
- $160,000 - $200,000 a year
Our compensations (cash and equity) are determined based on the position, your location, qualifications, and experience.
