Lucid Motors

Newark, CA, United States

Posted on: 2022-06-06

Category: emobility

Employment type:

Full time

Experience required:

Senior

Salary

Salary not provided

Sr. Data, ML Engineer

About the company:

Lucid is the new generation of EV. Our relentless focus on innovation, luxury, and sustainability drives us into a reality where you no longer have to choose between doing great things, doing the right thing, and doing everything with the highest regard for efficiency and design. There were luxury cars, then EVs, now there’s Lucid.  

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.

Senior Machine Learning and Data Engineer is responsible to build Machine learning applications, for both Vehicle and Operational data, building, tarining and running ML models. This hands-on role helps solve real big data problems, which most of the standard tools on the market are not capable of handling. You will be designing solutions, writing codes and automation, defining standards, and establish best practices across the company. 


• Design and develop ML pipeline using PySprak, Scala, SQL or Python.
• Deployment of large scale ML pipeline using open source technologies such as Kubeflow, MLFlow, Airflow
• Drive predictive analytics from billions of time series data points
• Articulate business questions and use mathematical techniques to arrive at an answer using data. Translate analysis results into business recommendations.
• Design and build the next generation of ML architecture that will power large-scale data science projects
• Adapt machine learning and data mining algorithms to solve problems across several teams
• Perform model training, hyper parameter tuning and model parallelization and distributed training to achieve top performance for accuracy and latency
• Lead projects with hands-on analysis and modeling, drawing from multiple analytical methods to choose the right tool and right level of complexity appropriate for the challenge.
• Perform and streamline continuous model performance monitoring and debugging in production
• Perform research and utilize state-of-the-art and best practices for model compression, quantization and optimization for deployment
• Use industry best practice tools and processes such as Data Lake, Delta Lake, S3, Spark ETL, Airflow, Hive Catalog, Ranger, Redshift, Spline, Kafka, MQTT, Timeseries Database, Cassandra, Redis, Presto, Kubernetes, Docker, CI/CD, DevOps
• Contribute to the overall architecture, implementation and ongoing maintenance of our codebase
• Optimize the performance and scale our data ingestion and processing infrastructure to server ever-increasing volume.
• Translate big data and analytics requirements into data models that will operate at a large scale and high performance and guide the data analytics engineers on these data models.
• Provide direction and focus in areas of high ambiguity
• Mentoring junior team members



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.

Notice regarding COVID-19 vaccination requirement as a condition of gainful employment within the United States
At Lucid, we prioritize the health and wellbeing of our employees, families, and friends above all else. In response to the novel Coronavirus, and the increased transmissibility with recent variants, all new Lucid employees, whose job will be based in the United States, must provide original documentation confirming status as having received the prescribed inoculation (doses) based on the manufacturer's guidelines on their first day of employment.
 
Individuals seeking a medical and/or religious exemption from this requirement may be granted such an accommodation after submitting a formal request to and the subsequent review and approval thereof by our dedicated Covid-19 Response team.
 
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. 

The Role

  • Design and develop ML pipeline using PySprak, Scala, SQL or Python.
  • Deployment of large scale ML pipeline using open source technologies such as Kubeflow, MLFlow, Airflow
  • Drive predictive analytics from billions of time series data points
  • Articulate business questions and use mathematical techniques to arrive at an answer using data. Translate analysis results into business recommendations.
  • Design and build the next generation of ML architecture that will power large-scale data science projects
  • Adapt machine learning and data mining algorithms to solve problems across several teams
  • Perform model training, hyper parameter tuning and model parallelization and distributed training to achieve top performance for accuracy and latency
  • Lead projects with hands-on analysis and modeling, drawing from multiple analytical methods to choose the right tool and right level of complexity appropriate for the challenge.
  • Perform and streamline continuous model performance monitoring and debugging in production
  • Use industry best practice tools and processes such as Data Lake, Delta Lake, S3, Spark ETL, Airflow, Hive Catalog, Ranger, Redshift, Spline, Kafka, MQTT, Timeseries Database, Cassandra, Redis, Presto, Kubernetes, Docker, CI/CD, DevOps
  • Contribute to the overall architecture, implementation and ongoing maintenance of our codebase
  • Translate big data and analytics requirements into data models that will operate at a large scale and high performance and guide the data analytics engineers on these data models.
  • Qualifications

  • B.S. or M.S. degree n Computer Science, or equivalent.
  • 6+ years of hands-on experience in ML pipeline, ETL, data modeling processing
  • 3+ years of hands-on experience in productionizing and deploying ML applications. 
  • Expert in Spark, Kafka, Presto, Kubeflow, Airflow, or similar technologies. 
  • Proficiency with machine/deep learning frameworks such as TensorFlow, Keras, Pytorch, Caffe, MXNet, etc
  • Experience in creating production level ML models for training, validation, and inference leveraging real-time systems
  • Experience with Kubernetes-based ML Architecture. 
  • Strong knowledge and understanding of machine learning pipelines from standardization, normalization, clustering, modeling, scoring, validation
  • Understanding of ETL engineering and tools so you can interface with data integration teams
  • Preferred Qualifications

  • Experience using Timeseries data
  • Experience with automotive data
  • Experience working with cloud-based accelerated computing, GPU/TPU, CUDA, parallel computing