Machine Learning Engineer at Canoo in Justin, TX
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 Plan, design, build and operationalize data and machine learning pipelines on a modern cloud data and ML stack. Work in an agile team environment across many business verticals to build and operate a data and ML platform to collect, model, integrate and make data assets and data products available for self-service analytics, AI/ML and API use cases. This position will report to the Data Office. Responsibilities Design and build machine learning pipelines using statistical and machine learning techniques on a modern cloud data stack. Support production operations of a cloud-based data platform supporting multiple data assets, data products, models, and API's. Work with Data Scientists and Data Engineers to prepare datasets and engineer features for model training and deployment. Build data and ML pipelines leveraging best practices and integrating with data management tools and frameworks for security, governance, quality, and compliance. Work with business partners across many verticals to write Agile stories for data and ML engineering features. Qualifications Required Experience Bachelor's degree in an Engineering or Quantitative discipline. 4 or more years of experience in a hands-on data and ML engineering role. Deep experience with one or more AI and ML frameworks like TensorFlow, PyTorch, Scikit-Learn and/or Keras. Advanced level knowledge of SQL. Advanced level experience with Python. Working knowledge of one or more cloud platform data and analytics services like AWS. Experience with one or more cloud data warehouse platforms like Snowflake or RedShift. Experience with streaming frameworks like Kafka. Experience working in a fast-paced team environment. Experience working on agile data analytics teams. Experience building in and measuring data quality. Ability to learn and apply new technologies, methods, and patterns. Experience with containerization. Experience with CI/CD. Automotive industry experience. Preferred Experience Masters in an Engineering or Quantitative discipline. AI/ML certifications on AWS, Google, or Azure. Snowflake experience and certifications. Experience working with high velocity streaming data. Experience with automotive telematics, video and ADAS data. AI/ML experience in Automotive industry. Experience with edge computing. Travel Requirements Travel limited to 10%. Physical Requirements for Non-Physical Positions 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 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
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine LearningEstimated Salary: $20 to $28 per hour based on qualifications.
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 Plan, design, build and operationalize data and machine learning pipelines on a modern cloud data and ML stack. Work in an agile team environment across many business verticals to build and operate a data and ML platform to collect, model, integrate and make data assets and data products available for self-service analytics, AI/ML and API use cases. This position will report to the Data Office. Responsibilities Design and build machine learning pipelines using statistical and machine learning techniques on a modern cloud data stack. Support production operations of a cloud-based data platform supporting multiple data assets, data products, models, and API's. Work with Data Scientists and Data Engineers to prepare datasets and engineer features for model training and deployment. Build data and ML pipelines leveraging best practices and integrating with data management tools and frameworks for security, governance, quality, and compliance. Work with business partners across many verticals to write Agile stories for data and ML engineering features. Qualifications Required Experience Bachelor's degree in an Engineering or Quantitative discipline. 4 or more years of experience in a hands-on data and ML engineering role. Deep experience with one or more AI and ML frameworks like TensorFlow, PyTorch, Scikit-Learn and/or Keras. Advanced level knowledge of SQL. Advanced level experience with Python. Working knowledge of one or more cloud platform data and analytics services like AWS. Experience with one or more cloud data warehouse platforms like Snowflake or RedShift. Experience with streaming frameworks like Kafka. Experience working in a fast-paced team environment. Experience working on agile data analytics teams. Experience building in and measuring data quality. Ability to learn and apply new technologies, methods, and patterns. Experience with containerization. Experience with CI/CD. Automotive industry experience. Preferred Experience Masters in an Engineering or Quantitative discipline. AI/ML certifications on AWS, Google, or Azure. Snowflake experience and certifications. Experience working with high velocity streaming data. Experience with automotive telematics, video and ADAS data. AI/ML experience in Automotive industry. Experience with edge computing. Travel Requirements Travel limited to 10%. Physical Requirements for Non-Physical Positions 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 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
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine LearningEstimated Salary: $20 to $28 per hour based on qualifications.
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