Sr. Machine Learning Engineer

Rivian-posted 4 months ago
$149,800 - $203,500/Yr
Full-time • Mid Level
Irvine, CA
Transportation Equipment Manufacturing
Resume
Match Score
Upload and Match ResumeTrack Jobs with Teal

Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract. As a company, we constantly challenge what's possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations. We are seeking a talented and driven Sr. Machine Learning Engineer to join our dynamic Supply Chain team. This is an exciting opportunity for someone with a few years of practical experience out of college who is passionate about applying machine learning, data science, and data engineering principles to solve complex real-world problems in a fast-paced automotive environment. You will play a crucial role in developing, deploying, and maintaining ML-powered solutions that enhance the efficiency, resilience, and intelligence of our supply chain.

  • Collaborate with stakeholders to understand supply chain challenges and design, develop, and implement machine learning models (e.g., forecasting, optimization, anomaly detection, predictive maintenance) to address them.
  • Work with large, complex datasets from various sources, performing data cleaning, transformation, and feature engineering to prepare data for model training and deployment.
  • Design, build, and maintain robust MLOps pipelines to effectively deploy, monitor, and manage machine learning models in production environments.
  • Contribute to the development and optimization of scalable data pipelines to ingest, process, and store supply chain data, ensuring data quality and accessibility for ML applications.
  • Design, implement, and maintain CI/CD/CT (Continuous Integration/Continuous Delivery/Continuous Training) pipelines to automate the testing, validation, and deployment of models and the underlying infrastructure.
  • Work closely with data scientists, data engineers, supply chain experts, and other cross-functional teams to translate business requirements into technical solutions and communicate findings effectively.
  • Implement comprehensive monitoring solutions for both model performance (accuracy, drift, bias) and operational health (latency, throughput, error rates, cost). Develop automated alerting and response strategies.
  • Build and manage scalable ML infrastructure on cloud platforms using IaC principles and tools (e.g., Terraform, Databricks DABs).
  • Stay current with the latest advancements in machine learning, data science, and supply chain technologies, and explore new approaches to solve emerging challenges.
  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Operations Research, Statistics, or a related quantitative field.
  • 3-5 years of practical experience in machine learning engineering, data science, or data engineering roles.
  • Strong programming proficiency in Python.
  • Experience with machine learning frameworks/libraries such as scikit-learn, TensorFlow, PyTorch.
  • Solid understanding of relational databases (SQL) and experience with big data technologies (e.g., Spark, Hadoop, Snowflake, Databricks).
  • Hands-on experience building production ML systems using tools like MLflow, Kubeflow, Vertex AI, or SageMaker for experiment tracking, model registry, and serving.
  • Familiarity with cloud platforms (Databricks, AWS, Azure, GCP) and their relevant services for ML and data.
  • Experience with DevOps principles and tools (e.g., Docker, Kubernetes, CI/CD pipelines like Jenkins, GitLab CI, GitHub Actions) for infrastructure as code and automated deployments.
  • Experience with Infrastructure as Code tools (e.g., Terraform, Databricks DABs) is highly desirable.
  • Experience with version control systems (e.g., Git).
  • Solid understanding of statistical modeling, machine learning algorithms, and experimental design.
  • Basic understanding of data warehousing concepts, ETL processes, and data governance.
  • Excellent analytical and problem-solving skills with a keen eye for detail.
  • Genuine interest in supply chain operations and the automotive industry, particularly electric vehicles.
  • Ability to clearly articulate complex technical concepts to both technical and non-technical audiences.
  • Experience with supply chain optimization, logistics, or manufacturing data.
  • Knowledge of simulation or optimization software.
  • Robust medical/Rx, dental and vision insurance packages for full-time employees, their spouse or domestic partner, and children up to age 26.
  • Coverage is effective on the first day of employment, and Rivian covers most of the premiums.
Track Jobs with Teal

Job Search Resources

•
AI Resume Builder
•
Machine Learning Engineer Resume Examples
•
Machine Learning Engineer Cover Letter Examples

Tools

Career Hubs

Guides

Company

© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service