Lucid Motors

Staff Machine Learning Engineer

Newark, CA
USD 163k - 240k
Spark Torch Keras API Python Kafka Kubernetes SQL TensorFlow Scala Java C++ Machine Learning Hadoop Docker
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Description
Leading the future in luxury electric and mobility
At Lucid, we set out to introduce the most captivating, luxury electric vehicles that elevate the human experience and transcend the perceived limitations of space, performance, and intelligence. Vehicles that are intuitive, liberating, and designed for the future of mobility.
 
We plan to lead in this new era of luxury electric by returning to the fundamentals of great design – where every decision we make is in service of the individual and environment. Because when you are no longer bound by convention, you are free to define your own experience.
 
Come work alongside some of the most accomplished minds in the industry. Beyond providing competitive salaries, we’re providing a community for innovators who want to make an immediate and significant impact. If you are driven to create a better, more sustainable future, then this is the right place for you.

The Data Science and Machine Learning team at Lucid is on the mission to design, develop, and deploy AI solutions to help make safe and sustainable products and services on par with Lucid’s Luxury brand. The Data Science Solutions Engineer at Lucid is setting data science pipeline for our fast growing data team. Data generated by electric vehicles is a rich and diverse and driving insight from them is a very exciting and challenging task. This opportunity involves architecting the data and ML pipeline to discover trends, patterns and hidden insights from the data while collaborating with the most brilliant talents in the automotive industry.  
 

The Role

  • Adapt machine learning and data mining algorithms to solve problems across several teams.
  • Design and build data architecture for data science projects using big data technologies.
  • Help define analytical direction and influence direction of the associated engineering and infrastructure work.
  • Implement and deploy Data Science models in production.
  • Help design and implement efficient software and contribute to the team’s code base through SDLC best practices.
  • Design metrics, reports, dashboards and BI solutions for data quality, and various data science applications
  • Work on state-of-the-art large-scale machine learning and GenAI projects involving LLMs.
  • Help derive predictive analytics from billions of time series data points.
  • Partner with internal stakeholders on projects to identify and articulate opportunities, see beyond data to identify solutions that will raise the bar for decision making.
  • Engage broadly with the organization to identify, prioritize, frame, and structure complex and ambiguous challenges, where advanced AI projects or tools can have the biggest impact.

Qualifications

  • Bachelors, Masters or PhD in Engineering, Computer Science, or related field.
  • 5+ years of SW, Data Science/ML or Data Engineering experience working on highly complex problems in a dynamic setting
  • Strong programming skills, especially in Python, Scala or Java, or C/C++ with 3+ years of relevant experience in a programming intensive role.
  • Technical knowledge of Statistics, and Machine Learning.
  • Advanced expertise in SQL.
  • Relevant work experience, including experience applying advanced analytics, and data mining techniques.
  • Hands-on Experience in Big Data and cloud technologies tools, i.e. Hadoop, Hive, Iceberg, Kafka, Spark, Presto, Airflow, Elastic Search, Docker and Kubernetes.
  • Experience with data presentation and visualization with tools such as Tableau, Grafana or other similar tools.
  • Excellent communication and presentation skills.

Nice to Haves

  • Experience with data science packages such as skit-learn, SciPy etc., and Machine Learning frameworks such as TensorFlow, Keras and Torch or LLMs.
  • Experience with REST API design, deploying and monitoring models in production.
  • Experience with telematics data engineering and/or analytics is a plus.
  • Experience with cloud tech-stack (e.g. K8s, docker, orchestration tools, CICD, etc.) is a big plus
Salary Range: The compensation range for this position is specific to the locations listed below and is the range Lucid reasonably and in good faith expects to pay for the position taking into account the wide variety of factors that are considered in making compensation decisions, including job-related knowledge; skillset; experience, education and training; certifications; and other relevant business and organizational factors.
·       California (Bay Area) - $163,700 - $240,020
 
Additional Compensation and Benefits: Lucid offers a wide range of competitive benefits, including medical, dental, vision, life insurance, disability insurance, vacation, and 401k. The successful candidate may also be eligible to participate in Lucid’s equity program and/or a discretionary annual incentive program, subject to the rules governing such programs.  (Cash or equity incentive awards, if any, will depend on various factors, including, without limitation, individual and company performance.)

Lucid maintains your privacy according to its Candidate Privacy Notice. If you are a California resident, please refer to our California Candidate Privacy Notice.

At Lucid, we don’t just welcome diversity - we celebrate it! Lucid Motors is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, national or ethnic origin, age, religion, disability, sexual orientation, gender, gender identity and expression, marital status, and any other characteristic protected under applicable State or Federal laws and regulations.
 
To all recruitment agencies: Lucid Motors does not accept agency resumes. Please do not forward resumes to our careers alias or other Lucid Motors employees. Lucid Motors is not responsible for any fees related to unsolicited resumes. 
Lucid Motors
Lucid Motors
Automotive Autonomous Vehicles Electric Vehicle Transportation

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