Software Engineer, Machine Learning Infrastructure (Autonomy)

Palo Alto, CA

Full Time
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Posted 1 week ago

At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

We care deeply about delivering the best transportation experience; this means the best experience for the passenger and the best experience for the driver. We believe this quality of service can only be achieved with a deep understanding of our world, our cities, our streets… how they evolve, how they breathe. We embrace the powerful positive impact autonomous transportation will bring to our everyday lives and with our ambition, we will become a leader in the development and operation of such vehicles. Thanks to our network, with hundreds of millions of rides every year, we have the means to make autonomy a safe reality. As a member of Level 5, you will have the opportunity to develop and deploy tomorrow’s hardware & software solutions and thereby revolutionize transportation.

As a machine learning infrastructure engineer, you will work directly with our autonomy and research teams to build and improve our mission critical machine learning systems. You will work in a fast paced environment and interact with a wide variety of teams ranging from ML researchers to cloud engineers. The ideal candidate should be well versed in the fundamentals of machine learning such as gradient computation in modern ML frameworks and distributed training concepts. Your work will directly contribute to our team’s ability to build and deploy a state of the art deep learning system for autonomous driving. 

Responsibilities:
  • Build and scale our PyTorch based machine learning system that powers all deep learning systems on the AV and on the cloud at Level 5
  • Be a champion for model and data code quality and maintain a high standard when shipping new features
  • Tackle unsolved problems at the intersection of ML algorithms and infrastructure such as optimizing large scale distributed training dynamics, multitask learning and sampling 
  • Willingness to learn and dive deep into unknown areas in machine learning, high-performance computing, and cloud infrastructure
  • Focus on delivering impact to our customers
Experience:
  • Bachelors in Computer Science or a related field
  • Experience in building large scale backend systems or working with ML infrastructure
  • Experience working with Python and C++
  • Detailed understanding of the ML lifecycle: data preprocessing, modeling, training, evaluation, and edge/cloud inference
  • Experience working with cloud infrastructure such as AWS, GCP, and Kubernetes
  • Basic understanding of ML algorithms
  • (Nice to have) Background in high-performance computing (HPC), optimization, or simulation
  • (Nice to have) Familiarity with parallel programming libraries such as MPI
  • (Nice to have) Have one or more high profile publications in ML
Benefits:
  • Great medical, dental, and vision insurance options
  • Mental health benefits
  • In addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off
  • 401(k) plan to help save for your future
  • 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
  • Pre-tax commuter benefits
  • Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity/affirmative action employer committed to an inclusive and diverse workplace. All qualified applicants will receive consideration for employment  without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law. 

Job tags: Autonomous Driving AWS Deep Learning Kubernetes Machine Learning ML Python PyTorch Research
Job region(s): North America
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