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.