Build secure, deployable AI systems for industries where precision matters

Want to implement cutting-edge AI solutions for high-stakes industries? This role combines ML engineering expertise with real-world impact in aerospace, healthcare, manufacturing and defence.

You'll join a small but fast-growing engineering team at a well-funded startup transforming how regulated industries leverage AI. Founded by successful entrepreneurs with billion-dollar exits, they've secured $20M and are already working with Fortune 500 clients where standard AI approaches fall short.

This role offers a unique chance to work on AI challenges with meaningful real-world impact, with access to abundant compute resources for complex development. You'll help shape technical direction as an early team member, balancing practical implementation with cutting-edge ML research across multiple high-value industries in a no-ego culture focused on building working solutions.

As an ML Engineer, you'll bridge the gap between research and practical implementation, ensuring sophisticated AI models work reliably in mission-critical environments.

Your focus:

• Implementing and optimizing models for specific client needs across regulated industries
• Building models (NLP or Computer Vision - depending on your background)
• Working with LLMs, such as API integrations, fine-tuning and prompting
• Developing client-specific models and adapting solutions using transfer learning
• Conducting evaluations and handling customer data onboarding
• Collaborating with the Applied AI team to operationalize research breakthroughs

You should have:

• 5+ years of experience in ML or software engineering with ML focus
• Good practical experience in PyTorch or TensorFlow
• Experience deploying ML models in production environments
• Solid AWS knowledge (or comparable cloud platform expertise)
• Python proficiency and familiarity with ML deployment challenges

Nice to have:

• Computer vision or NLP expertise
• Experience in regulated industries (healthcare, aerospace, defence)
• Experience with Kubernetes
• Prior work with MLOps tooling and practices
• Science/engineering degree (Masters preferred)

They offer:

• Competitive salary ($180k-$225k depending on experience) plus bonus potential
• Significant equity package
• Comprehensive healthcare (medical, dental, vision)
• 401k contributions
• 20 days vacation and flexible working arrangements

You'll need to be based in the US – Seattle or Miami (attractive relocation package provided for Florida).

If building secure, practical AI systems for industries where decisions truly matter appeals to you, reach out for a confidential conversation. All applicants will receive a response.