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.