Rivian
Overview
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Sr. Machine Learning Engineer
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Rivian . Role Summary: 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. Responsibilities
Design and Develop ML Models: 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. Data Preparation & Feature Engineering: Work with large, complex datasets from various sources, performing data cleaning, transformation, and feature engineering to prepare data for model training and deployment. Model Deployment & MLOps: Design, build, and maintain robust MLOps pipelines to effectively deploy, monitor, and manage machine learning models in production environments. This includes setting up automated model retraining, versioning, and performance tracking. Data Pipeline Development: 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. CI/CD for Machine Learning: 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. Collaboration & Communication: 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. Advanced Monitoring & Observability: 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. Infrastructure as Code (IaC): Build and manage scalable ML infrastructure on cloud platforms using IaC principles and tools (e.g., Terraform, Databricks DABs). Research & Innovation: Stay current with the latest advancements in machine learning, data science, and supply chain technologies, and explore new approaches to solve emerging challenges. Qualifications
Education: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Operations Research, Statistics, or a related quantitative field. Experience: 3-5 years of practical experience in machine learning engineering, data science, or data engineering roles. Technical Skills: 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). MLOps Platforms: 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). Data Science Fundamentals: Solid understanding of statistical modeling, machine learning algorithms, and experimental design. Data Engineering Acumen: Basic understanding of data warehousing concepts, ETL processes, and data governance. Problem-Solving: Excellent analytical and problem-solving skills with a keen eye for detail. Domain Interest: Genuine interest in supply chain operations and the automotive industry, particularly electric vehicles. Communication: Ability to clearly articulate complex technical concepts to both technical and non-technical audiences. Bonus Points (Nice To Have)
Experience with supply chain optimization, logistics, or manufacturing data. Knowledge of simulation or optimization software. Pay Disclosure
Salary Range/Hourly Rate for California Based Applicants: $149,800 - $203,500 (actual compensation will be determined based on experience, location, and other factors permitted by law). Salary Range/Hourly Rate for Illinois & Michigan Based Applicants: $143,300 - $179,100 (actual compensation will be determined based on experience, location, and other factors permitted by law). Benefits Summary: Rivian provides 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. Equal Opportunity
Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law. Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us at candidateaccommodations@rivian.com. Candidate Data Privacy
Rivian may collect, use and disclose your personal information or personal data (within the meaning of the applicable data protection laws) when you apply for employment and/or participate in our recruitment processes. This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information. Rivian may use your Candidate Personal Data for the purposes of tracking interactions with our recruiting system; carrying out, analyzing and improving our application and recruitment process; establishing an employment relationship; complying with legal obligations; recordkeeping; ensuring network and information security; and other permitted activities. Rivian may share your Candidate Personal Data with internal personnel, Rivian affiliates, and Rivian’s service providers. Rivian may transfer or store internationally your Candidate Personal Data to jurisdictions including the United States, Canada, the United Kingdom, and the European Union. This data may be subject to local laws and accessible to authorities. Please note that we are currently not accepting applications from third party application services. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries
Motor Vehicle Manufacturing
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Join to apply for the
Sr. Machine Learning Engineer
role at
Rivian . Role Summary: 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. Responsibilities
Design and Develop ML Models: 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. Data Preparation & Feature Engineering: Work with large, complex datasets from various sources, performing data cleaning, transformation, and feature engineering to prepare data for model training and deployment. Model Deployment & MLOps: Design, build, and maintain robust MLOps pipelines to effectively deploy, monitor, and manage machine learning models in production environments. This includes setting up automated model retraining, versioning, and performance tracking. Data Pipeline Development: 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. CI/CD for Machine Learning: 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. Collaboration & Communication: 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. Advanced Monitoring & Observability: 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. Infrastructure as Code (IaC): Build and manage scalable ML infrastructure on cloud platforms using IaC principles and tools (e.g., Terraform, Databricks DABs). Research & Innovation: Stay current with the latest advancements in machine learning, data science, and supply chain technologies, and explore new approaches to solve emerging challenges. Qualifications
Education: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Operations Research, Statistics, or a related quantitative field. Experience: 3-5 years of practical experience in machine learning engineering, data science, or data engineering roles. Technical Skills: 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). MLOps Platforms: 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). Data Science Fundamentals: Solid understanding of statistical modeling, machine learning algorithms, and experimental design. Data Engineering Acumen: Basic understanding of data warehousing concepts, ETL processes, and data governance. Problem-Solving: Excellent analytical and problem-solving skills with a keen eye for detail. Domain Interest: Genuine interest in supply chain operations and the automotive industry, particularly electric vehicles. Communication: Ability to clearly articulate complex technical concepts to both technical and non-technical audiences. Bonus Points (Nice To Have)
Experience with supply chain optimization, logistics, or manufacturing data. Knowledge of simulation or optimization software. Pay Disclosure
Salary Range/Hourly Rate for California Based Applicants: $149,800 - $203,500 (actual compensation will be determined based on experience, location, and other factors permitted by law). Salary Range/Hourly Rate for Illinois & Michigan Based Applicants: $143,300 - $179,100 (actual compensation will be determined based on experience, location, and other factors permitted by law). Benefits Summary: Rivian provides 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. Equal Opportunity
Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law. Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us at candidateaccommodations@rivian.com. Candidate Data Privacy
Rivian may collect, use and disclose your personal information or personal data (within the meaning of the applicable data protection laws) when you apply for employment and/or participate in our recruitment processes. This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information. Rivian may use your Candidate Personal Data for the purposes of tracking interactions with our recruiting system; carrying out, analyzing and improving our application and recruitment process; establishing an employment relationship; complying with legal obligations; recordkeeping; ensuring network and information security; and other permitted activities. Rivian may share your Candidate Personal Data with internal personnel, Rivian affiliates, and Rivian’s service providers. Rivian may transfer or store internationally your Candidate Personal Data to jurisdictions including the United States, Canada, the United Kingdom, and the European Union. This data may be subject to local laws and accessible to authorities. Please note that we are currently not accepting applications from third party application services. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries
Motor Vehicle Manufacturing
#J-18808-Ljbffr