Machine Learning Engineer

About the role

Step into the Copilot DFM team and take ownership of the core intelligence layer that drives automated manufacturing innovation. You will architect and refine vision-language models that decode intricate manufacturing data, allowing our factories to produce essential components with increased speed and reduced cost. This position grants you end-to-end responsibility for ML lifecycles, bridging the gap between theoretical research and real-world deployment. Your work will directly influence factory throughput and the reliability of critical part production. You will challenge existing paradigms by introducing smarter data interpretation techniques that replace outdated, linear workflows. Expect to operate with a high degree of autonomy, shaping the technical roadmap alongside product stakeholders. Your decisions will have a direct impact on the scalability and efficiency of our manufacturing systems. By joining this team, you commit to building the intelligent backbone of a modern factory floor.

Key facts

What you'll do

• Architect and deploy multimodal models that ingest and interpret manufacturing documentation, replacing legacy sequential processing pipelines.
• Partner with core engineering to design annotation interfaces, implement active learning loops, and construct synthetic data generation frameworks.
• Engineer comprehensive evaluation suites that analyze system behavior and quantifying user impact, moving past conventional benchmark reliance.
• Liaise with fellow machine learning specialists to chart the technical and product trajectory of the AI platform.
• Drive model accuracy enhancements that unlock substantial time savings across critical manufacturing workflows.
• Define data strategies that improve the signal-to-noise ratio within complex manufacturing datasets.
• Implement robust monitoring to detect model drift and ensure consistent performance in dynamic production environments.
• Translate ambiguous product requirements into concrete model objectives and success criteria.
• Lead experiments that test novel model architectures against real-world manufacturing constraints.
• Document model behavior and decision pathways to ensure transparency for operations teams.

Requirements

• Demonstrate 5-8 years of professional deep learning experience in a production setting.
• Show at least 2 years of hands-on work with multimodal models that fuse image and text data streams.
• Exhibit strong proficiency in Python and PyTorch, including the ability to write custom training loops, loss functions, and data loaders.
• Prove experience in owning the full production deployment of models, including vigilance over endpoint and model health.
• Hold an MS or PhD in Computer Science, Electrical Engineering, or a related field, with equivalent industry experience viewed as equally acceptable.
• Display a meticulous approach to debugging and optimizing neural network performance under tight deadlines.
• Validate a solid understanding of software engineering best practices, including version control and testing methodologies.
• Confirm eligibility to work in the United States under ITAR regulations, which necessitate citizenship, lawful permanent residency, protected individual status, or required authorizations.

Nice to have

• Show a genuine interest in manufacturing and a firm belief that software can elevate the industry to new heights.
• Bring previous experience from aerospace, defense, or manufacturing sectors, specifically involving manufacturing data complexities.
• Include published research that achieved state-of-the-art results on relevant benchmarks or contributions to widely used open-source frameworks.
• Highlight prior experience thriving in a high-ownership startup environment where agility and impact are paramount.
• Demonstrate comfort with fast-paced iteration and the ability to pivot based on empirical evidence.

Practical notes

• This role requires U.S. citizenship, lawful permanent residency, protected individual status, or specific authorization to comply with ITAR regulations.
• The position is based in Los Angeles, California, and requires physical presence in the office.
• Full-time engagement is expected, with standard business hours applying.
• Travel is not required for this role.
• Candidates should be aware that Hadrian utilizes AI-assisted tools during the recruiting process to improve efficiency.
• All final hiring decisions are conducted exclusively by human recruiters and hiring managers.
• Candidates will be notified if any portion of the interview is recorded, and they retain the right to opt out of recording.
• Comprehensive benefits include medical, dental, vision, and life insurance packages.
• The role offers a 401k retirement plan with potential company match.
• Flexible vacation policies are provided to support work-life balance.
• Equity participation may be offered as part of the total compensation package.
• Relocation support is available for qualified candidates moving to the Los Angeles area.
• The posting remains open until the position is filled, encouraging early applications for consideration.