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.
As a Deep Learning Optimization Engineer you will be a member of the Deep Learning team at Rivian, which develops advanced machine learning algorithms that directly impact safety and self-driving features of our vehicles. One of the core responsibilities of the team is to create the infrastructure needed to support CI/CD of Deep learning algorithms and enable large scale distributed training.
- Develop and support Deep learning/ Machine Learning algorithms such as optimization in large scale distributed training, Neural Architecture Search, domain adaptation, multitask learning, intelligent sampling, and active learning
- Resource-aware optimizations for Deep learning Models to improve latency and memory utilization
- Identify and resolve DL model inference bottlenecks on embedded platform by evenly distribution of compute across layers
- Support mixed precision DL model training/development and deployment of the model on embedded system.
- Collaborate with Infra team to support CI/CD tooling and interfaces to support rapid benchmarking, analysis and optimization of our inference models, hyper-parameter tuning, and data visualization.
- MS. or Ph.D. in Electrical, Mechanical, or Aerospace Engineering, Computer Science, or a related field
- 3+ years of experience
- Research and development experience in one or more of the following areas:
- AutoML, NAS, Evolutionary Architecture Search
- Optimizing and deploying inference on embedded processors
- Experience working on GPU clusters/ training at scale on cloud
- Experience defining compute architecture for efficient Deep learning inferencing
- Strong Python programming background
- Good Understand the fundamentals of Deep learning with industrial experience
- Experience with frameworks such as TensorFlow, MxNet, PyTorch.
- Familiarity with DL model optimization strategies such as pruning, quantization, AutoML for model compression, Neural Architecture Search
- Ability to work in a fast-paced development environment
- Good team player with great communication skills
- Passionately motivated to take ideas from R&D phase to a product
- Productization of inference models on embedded platforms
- Experience with training and network optimization
- Experience in automotive applications
- Prototyping real-time applications
- Software development for safety critical systems (ISO 26262)
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.
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