Machine Learning Engineer — AI Architecture Research
- Firma
- Featherless AI
- Lokacija
- Remote
- Nivo
- Mid
- Objavljeno
- 28.09.2026
Opis posla
ABOUT THE ROLE
We’re looking for a Machine Learning Engineer focused on AI architecture research to help design, prototype, and validate next-generation model architectures. You’ll work at the intersection of research and production — turning new ideas into scalable, real-world systems.
This role is ideal for someone who enjoys questioning architectural assumptions, experimenting with novel model designs, and pushing beyond standard Transformer-style approaches.
WHAT YOU’LL WORK ON
- Research and develop new neural network architectures (e.g. alternatives or extensions to Transformers, recurrent / hybrid models, long-context systems)
- Design and run architecture-level experiments (scaling laws, memory mechanisms, compute trade-offs)
- Prototype models end-to-end — from research code to training-ready implementations
- Collaborate with inference and systems engineers to ensure architectures are deployable and efficient
- Analyze model behavior, failure modes, and inductive biases
- Read, reproduce, and extend cutting-edge research papers
- Contribute to internal research notes, benchmarks, and open-source efforts (where applicable)
WHAT WE’RE LOOKING FOR
- Strong background in machine learning fundamentals and deep learning
- Hands-on experience implementing model architectures from scratch
- Solid understanding of:
- Attention mechanisms, RNNs, state-space models, or hybrid architectures
- Training dynamics, scaling behavior, and optimization
- Memory, latency, and compute constraints at the model level
- Comfortable working in PyTorch or JAX
- Ability to move fluidly between theory, experimentation, and engineering
- Clear communicator who can explain architectural trade-offs
NICE TO HAVE
- Experience with non-Transformer architectures (RNN variants, SSMs, long-context models)