Adaption Labs
Applied ML Engineer
About this role
An Applied ML Engineer role focused on solving high-impact customer problems by building tailored ML solutions that bridge gaps between the platform and real-world needs. You'll work directly with strategic customers across diverse domains, translating field insights into product innovation while maintaining ownership from discovery through deployment.
What you'll do
- Identify high-leverage opportunities in customer problems and data workflows to build differentiated ML solutions
- Develop production-grade ML systems to address product gaps discovered through customer engagement
- Design and implement efficient, adaptive ML architectures across varied production environments and customer tech stacks
- Partner strategically with customers from problem discovery through solution deployment, ensuring accountability for results
- Create technical demonstrations and deliver presentations to senior stakeholders to communicate impact
What they're looking for
- Machine learning frameworks (PyTorch, JAX, TensorFlow)
- Software engineering and systems-level design for AI
- Data modeling and understanding how data curation impacts model performance
- Customer-facing technical communication and stakeholder management
- Online learning, reinforcement learning, or efficient ML architectures (bonus)
- Model training with human feedback and adaptive learning techniques (bonus)
Benefits
- Flexible work arrangements with in-person Bay Area collaboration and global-first distributed options
- Adaption Passport: annual travel stipend to explore new countries
- Weekly lunch stipend for take-out or grocery delivery
- Comprehensive medical benefits
- Generous paid time off
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Adaption Labs
Adaption Labs builds machine learning systems and infrastructure that solve real-world customer problems at scale, from efficient AI inference to production ML deployments. The company is hiring Applied ML Engineers, distributed systems engineers, and research-focused technologists to develop adaptive AI solutions and bridge the gap between experimental research and reliable, deployed systems.
View all jobs at Adaption LabsLikely interview questions
- Walk us through a time you identified a gap between what a product offered and what a customer actually needed—how did you approach building the solution?
- Describe your experience working with different ML frameworks (PyTorch, JAX, TensorFlow). How have you chosen between them for different projects?