Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.
As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.
Rivian’s Self-Driving Cloud Team is responsible for the end-to-end implementation of cloud digital experiences across web and mobile apps, scalable data services and machine learning at scale. To that end, we are developing a world-class cloud services platform that will support implementing fully autonomous self-driving for Rivian vehicles. We are seeking an ML Ops Engineer who will be developing tools and processes to manage machine learning and compute services at scale and help deploy and manage data services using the latest cloud services technologies on AWS. You’ll be building ML infrastructure from code with an obsession towards helping the Self-Driving team go as fast as possible and manage petabytes of sensor data.
This is what you’ll do:
- Design and build effective, user-friendly infrastructure, tooling, and automation to accelerate Machine Learning at Rivian ADAS organization
- Collaborate with teams to drive the ML technical roadmap
- Collaborate with Machine Learning Engineers and Product Managers to develop tools to support experimentation, training and production operations
- Build and maintain data pipelines using tools like Databricks, Python, Golang and Airflow
- Offer support and troubleshooting assistance for the ML pipeline, while continuously improving stability along the way
- Build and maintain systems employing an Infrastructure-as-Code (Terraform, CDK, or cloud formation) approach
- Establish standards and practices around MLOps, including governance, compliance, and data security
- Collaborate on managing ML/DL infrastructure costs
This is what you’ll need:
- 2+ years of experience with ML infrastructure and ML DevOps
- 2+ years of overall engineering experience in distributed systems and data infrastructure
- 2+ years experience coding in Python (preferred) or other languages like Java, or Golang.
- 2+ years experience with AWS or other public cloud platforms (GCP, Azure, etc.)
- Experience working with ML engineers to build tooling and automation to support the entire ML engineering lifecycle, from experimentation to production operations
- Experience with implementing ML CI/CD workflows
- Knowledge of Agile Development of Accessible Software Tools
- Microservice oriented architectures (using EKS, AWS ECS or Docker swarm)
- Solid understanding of OSI model and networking concepts such as DNS, TCP/IP, DHCP, load balancing, routing ..etc.
- Experience AWS Sagemaker tool suite, Lambda, S3, RDS, DynamoDB, EFS, and FSX
- Excellent verbal and written communication skills.
- Master's Degree in related field or equivalent experience
- Linux internals, networking, and distributed computing
- AWS or Cloud Native certification
- Experience building production infrastructure from scratch
Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law.
Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us at firstname.lastname@example.org.
We take your privacy seriously. For details please see our Candidate Privacy Notice.
Please note that we are currently not accepting applications from third party application services.