Canoo Technologies Inc.

ADAS Engineer, SW Infrastructure, ML

ID
2022-2808
Category
Software Engineering
Type
Full Time
Location : Location
US-CA-Torrance
Additional Locations
US-TX-Justin
Telecommute
No

About Canoo

Canoo’s mission is to bring EVs to Everyone and build a world-class team to deploy this sustainable mobility revolution. We have developed breakthrough electric vehicles that are reinventing the automotive landscape with pioneering technologies, award-winning designs, and a unique business model that spans all owners in the full lifecycle of the vehicle. Canoo is starting production and is distinguished by its pioneering and experienced team of technologists, engineers, and designers. With offices around the country, the company is scaling quickly and seeking candidates who love to challenge themselves, are motivated by purpose, and possess a strong desire to get things done.

 

The “Canoo Way”

 

Canoo’s success is the direct result of our disciplined application of our core operating principles and drills, which are based on three main principles: Think 80/20 (“Important versus less important”), Act 30/30 (“Reduce waste and increase output”), and Live 90/10 (“We have each other’s back”). We hire based on “MET” - Mindset, Equipment and willingness to Train - and seek individuals that take accountability and deliver results while being Humble, Hungry to succeed, and Hunting for opportunities to win. We train our team to engage with each other by modulating between their intellect (iQ) and emotional intelligence (eQ), applying Facts, Finesse, and Force when they communicate. The principles and drills of the CANOO Way have been fundamental to our success, our ability to grow, continuously improve, innovate and are at the core of our day-to-day operations.

Overview

The ADAS team is looking for a passionate and highly motivated ML Engineer. The primary responsibility of this role are to design and implement scalable software infrastructure for ADAS feature development, build and maintain the end-to-end, scalable, and reliable ML pipeline, including data collection, pre-processing, model training, evaluation, and deployment, develop scalable distributed training and evaluation systems for deep learning models, and stay up-to-date with the latest developments in the MLOps field and apply them to improve our infrastructure.

Responsibilities

  • Bachelor’s degree in CS/EE or a related technical field
  • 2+ years related industrial experience.
  • Strong proficiency in Python
  • Experience with relevant ML libraries (e.g., PyTorch, TensorFlow).
  • Strong proficiency in Linux fundamentals and containerization of Linux environments
  • Strong experience with cloud platforms (e.g., AWS, GCP, Azure).
  • Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).
  • Experience with CI/CD tools (e.g., Jenkins, TravisCI) and version control systems (e.g., Git).
  • Experience with MLOPs frameworks such as MLflow/Kubeflow/Databricks
  • Experience with Infrastructure-as-code tools like Kubernetes, Terraform, Ansible
  • Self-motivated, comfortable operating without direct supervision
  • Strong written and verbal communications

#LI-SK1

Qualifications

Required Experience

  • Bachelor’s degree in CS/EE or a related technical field
  • 2+ years related industrial experience.
  • Strong proficiency in Python
  • Experience with relevant ML libraries (e.g., PyTorch, TensorFlow).
  • Strong proficiency in Linux fundamentals and containerization of Linux environments
  • Strong experience with cloud platforms (e.g., AWS, GCP, Azure).
  • Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).
  • Experience with CI/CD tools (e.g., Jenkins, TravisCI) and version control systems (e.g., Git).
  • Experience with MLOPs frameworks such as MLflow/Kubeflow/Databricks
  • Experience with Infrastructure-as-code tools like Kubernetes, Terraform, Ansible
  • Self-motivated, comfortable operating without direct supervision
  • Strong written and verbal communications

PreferredExperience  

  • Data annotation infrastructure or workflow for camera perception models
  • Distributed model training orchestration (container orchestrators and cluster management software)
  • Knowledge of embedded systems and experience integrating ML models into hardware.
  • Experience with Cloud Storage (e.g., S3), NoSQL database (e.g., MongoDB), Workflow schedulers (e.g., Airflow)
  • Experience with C++
  • Experience with full MLOPs lifecycles in Production
  • Experience with Model development experiment tracking
  • Experience with Deep learning model development, training, and evaluation for computer vision applications.

 Travel Requirements

  • None

Physical Requirements

  •  While performing the duties of this job, employees may be required to sit for prolonged periods of time, occasionally bending or stooping, lifting up to 10 pounds, and prolonged periods of computer use.

Reasonable Accommodations

  • Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of the position.

What's Cool About Working Here...

  • Meaningful, challenging work that will redefine the automotive landscape and make EVs available to everyone
  • Comprehensive Health Insurance
  • Equity Compensation
  • Flexible Paid Time Off
  • Casual workplace with an unbelievable feeling of energy

Canoo is an equal opportunity-affirmative action employer and considers all qualified applicants for employment based on business needs, job requirements and individual qualifications, without regard to race, color, religion, sex, age, disability, sexual orientation, gender identity or expression, marital status, past or present military service or any other status protected by the laws or regulations in the locations where we operate. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

 

Any unsolicited resumes or candidate profiles submitted in response to our job posting shall be considered the property of Canoo Inc. and its subsidiaries and are not subject to payment of referral or placement fees if any such candidate is later hired by Canoo unless you have a signed written agreement in place with us which covers the applicable job posting. 

 

Canoo maintains compliance with the OFCCP. As such, please feel free to review the following information:

 

https://www.dol.gov/agencies/ofccp/posters

 

https://www.dol.gov/agencies/olms/poster/labor-rights-federal-contractors

 

If you are a person with a disability needing assistance with the application process, please call (310) 702-7907 or email us at talentacquisitionteam@canoo.com

 

Salary will be determined based on a number of factors, including but not limited to years of experience, training, skillset, location, etc.  Expected salary range in CA: $108,800 - $130, 600 annually

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