Senior AI/ML Ops for Manufacturing Automation

Blue Origin

San Francisco (CA)

On-site

USD 231,000 - 323,000

Full time

42 hours ago

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Benefits offered by this job

Medical, dental, vision insurance

401(k) with company match

Paid parental leave

Stock options

Job summary

Blue Origin is seeking an experienced Software Engineer (AI/ML Ops) to advance automated manufacturing systems with robust deployment of ML models. You will collaborate with automation engineers, data scientists, and software teams to embed AI into production tooling and optimize data processing pipelines.

The role emphasizes building scalable infrastructure, implementing monitoring, and ensuring security and compliance across production AI systems.

Qualifications

Bachelor’s or higher in Computer Science, Software Engineering, Mechanical Engineering or a related field.
10+ years of professional software development experience, with a significant focus on real world machine learning deployments using vision and/or time-series data.
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 (e.g. Simatic NPU).
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).

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 AI/ML 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.