About the position
At Blue Origin, we envision millions of people living and working in space for the benefit of Earth. We're working to develop reusable, safe, and low-cost space vehicles and systems within a culture of safety, collaboration, and inclusion. Join our team of problem solvers as we add new chapters to the history of spaceflight! This role is part of Blue Origin Operations, which is comprised of Integrated Supply Chain, Test Operations, Safety, Quality, and Mission Assurance. This includes Manufacturing and Supply Chain support across all Blue Origin facilities. Our team is looking for outstanding, highly motivated Software Engineers (AI/ML Ops) to join our Automation Team. This role requires an individual with a deep understanding of software development as well as automated manufacturing processes, and a broad range of technical capabilities. AI will unlock the true potential of manufacturing automation, you will join our team of automation development engineers, working directly with them to embed AI in every system we create. We are looking for someone to apply their technical expertise, leadership skills, and commitment to quality to positively impact safe human spaceflight. Passion for our mission and vision is required!
Responsibilities
- Work directly with the automation engineering team to develop and implement strategies for seamless deployment of machine learning models into our automation products.
- Complete the operational aspects of AI and machine learning projects, ensuring robust and scalable deployment.
- Build and maintain the infrastructure required for efficient data processing, model training, and inference at scale.
- Set up and manage monitoring systems to ensure the performance, reliability, and scalability of AI/ML models in production.
- Automate the end-to-end machine learning pipeline, including data collection, preprocessing, model training, deployment, and monitoring.
- Work closely with data scientists, data engineers, and software engineers to streamline the workflow from development to production.
- Ensure that AI/ML systems comply with security standards and best practices, addressing data privacy and protection concerns.
- Conduct performance tuning, troubleshooting, and optimization of AI and ML models to improve efficiency and reduce latency.
- Evaluate, select, and integrate appropriate tools and frameworks for model training, deployment, and monitoring (e.g., MLflow, Kubeflow, TensorFlow Extended).
- Maintain comprehensive documentation of processes, configurations, and performance metrics of deployed AI/ML models.
- Foster a culture of continual improvement by staying updated with the latest advancements in AIML Ops and implementing best practices.
- Develop and implement incident response plans to address and mitigate issues with deployed models promptly.
- Plan and implement strategies for scaling AI/ML models to handle increased demand and larger datasets.
- Proactively propose new solutions and enhancements leveraging AI/ML to address business challenges and improve operational efficiency.
- Work with cross-functional teams to incorporate AI/ML insights into broader business strategies and processes.
Requirements
- Bachelor's or higher in Computer Science, Software Engineering, or a related field.
- 3+ years of professional software development experience, with a significant focus on AI/ML ops.
- Extensive experience with AI and machine learning tools and frameworks, such as TensorFlow, PyTorch, or similar.
- Familiarity with manufacturing automation, including robotics, PLC's, automated NDT, and machine vision.
- Experience with AI edge deployments and integration into OT devices.
- Advanced understanding of microservices architecture and best practices.
- Experience with serverless computing frameworks and technologies.
- Familiarity with software development in agile and scrum environments.
- Experience with database management systems, both SQL and NoSQL (e.g., PostgreSQL, MongoDB).
- Advanced knowledge of cybersecurity best practices and compliance issues.
- Strong project management skills with the ability to manage multiple priorities.
- Strong analytical and problem-solving skills with attention to detail.
- Excellent written and verbal communication skills for clear documentation and cross-team collaboration.
- Ability to innovate and adapt to rapidly changing technologies and environment.
Nice-to-haves
- Certifications such as AWS Certified DevOps Engineer, Google Cloud Professional DevOps Engineer, Certified Kubernetes Administrator (CKA), or similar.
Benefits
- Medical, dental, vision, basic and supplemental life insurance, paid parental leave, short and long-term disability.
- 401(k) with a company match of up to 5%, and an Education Support Program.
- Paid Time Off: Up to four (4) weeks per year based on weekly scheduled hours, and up to 14 company-paid holidays.
- Discretionary bonus: Bonuses are designed to reward individual contributions as well as allow employees to share in company results.
