Sr. Autonomous Manufacturing Systems Engineer

Blue Origin•Cupertino, CA

2d•$156,802 - $219,522

About The Position

This role is part of Blue Origin Operations, supporting manufacturing and supply chain across Blue Origin facilities. The Automation Team develops, deploys, and supports manufacturing automation systems, combining established and emerging technologies to support the company’s mission. The role partners with automation development engineers to embed AI/ML capabilities into manufacturing automation products and requires knowledge of software development and automated manufacturing processes and systems, including industrial automation hardware and software. The position owns operational aspects of AI/ML projects, from infrastructure and data processing through model training, deployment, monitoring, and incident response. It works with data scientists, data engineers, software engineers, and automation engineers to move AI/ML systems from development into production, with attention to security, privacy, reliability, scalability, performance, documentation, and continual improvement. The role also prototypes AI/ML solutions for business and operational challenges and mentors junior engineers. Blue Origin seeks candidates who are motivated by its spaceflight mission and committed to safety, collaboration, inclusion, and quality. Applicants must meet the stated U.S. citizenship or immigration-status requirement. The stated base pay range for California applicants is $156,802.00–$219,522.45; ranges at other sites may differ.

Requirements

5+ years of professional software development experience, with a focus on real-world machine learning deployments using vision and/or time-series data.
Hands-on experience with AI/ML tools and frameworks such as TensorFlow, PyTorch, or similar.
Strong analytical and problem-solving skills with attention to detail.
Strong written and verbal communication skills for documentation and cross-team collaboration.
Ability to innovate and adapt to rapidly changing technologies and environments.
Ability to earn trust, maintain positive and professional relationships, and contribute to a culture of inclusion.
Must be a U.S. citizen or national, U.S. permanent resident (current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

Nice To Haves

Bachelor's degree or higher in Computer Science, Software Engineering, Mechanical Engineering, or a related field.
Familiarity with manufacturing automation, including robotics, PLCs, automated NDT, and machine vision.
Experience with AI edge deployments and integration into OT devices, such as Simatic NPU.
Experience with serverless computing frameworks and technologies.
Experience working in agile and scrum environments.
Experience with SQL and NoSQL database systems, such as PostgreSQL and MongoDB.
Familiarity with tools and frameworks such as MLflow, Kubeflow, or TensorFlow Extended.

Responsibilities

Partner with the automation engineering team to design and implement approaches for deploying machine learning models into automation products.
Own the operational aspects of AI/ML projects and ensure robust, scalable deployment.
Build and maintain infrastructure for efficient data processing, model training, and inference at scale.
Implement and manage monitoring systems for production AI/ML model performance, reliability, and scalability.
Automate the end-to-end ML pipeline, including data collection, preprocessing, training, deployment, and monitoring.
Collaborate with data scientists, data engineers, and software engineers to streamline the transition from development to production.
Ensure AI/ML systems comply with security standards and best practices, including data privacy and protection.
Tune, troubleshoot, and optimize AI/ML models to improve efficiency and reduce latency.
Evaluate, select, and integrate tools and frameworks for model training, deployment, and monitoring.
Document processes, configurations, and performance metrics for deployed models.
Stay current with AI/ML Ops advancements and apply best practices to support continual improvement.
Develop and execute incident response plans for issues with deployed models.
Implement strategies to scale AI/ML models for increased demand and larger datasets.
Propose and prototype AI/ML solutions that address business challenges and improve operational efficiency.
Mentor junior engineers and collaborate across teams to incorporate AI/ML insights into broader processes.

Benefits

Medical, dental, and vision insurance.
Basic and supplemental life insurance.
Paid parental leave.
Short- and long-term disability.
401(k) with company match of up to 5%.
Education Support Program.
Stock options for regular employees working at least 20 hours per week.
Paid time off of up to four weeks per year based on weekly scheduled hours.
Up to 14 company-paid holidays.
Depending on role type and job level, employees may be eligible for benefits and bonuses, which are not guaranteed.