Featherless AI - Machine Learning Engineer — AI Architecture Research

Remote (world) - Hybrid+ Equity6mo ago

In Office WW Artificial Intelligence Machine Learning Engineer AI Engineer Customer Training JAX

Requirements

• 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 • Experience with non-Transformer architectures (RNN variants, SSMs, long-context models) • Background in research-driven startups or open-source ML projects • Experience with large-scale training or custom training loops • Publications, preprints, or notable research contributions • Familiarity with inference optimization and deployment constraints

Responsibilities

• Research and develop new neural network architectures. • Design and run architecture-level experiments focusing on 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 for deployable and efficient model designs. • Analyze model behavior, failure modes, and inductive biases. • Read, reproduce, and extend cutting-edge research papers in the field of machine learning. • Contribute to internal research notes, benchmarks, and open-source efforts where applicable.

Benefits

• Work on core model architecture, not just fine-tuning • Direct influence on the technical direction of a Series-A company • Small, high-caliber team with fast feedback loops • Opportunity to ship research into production • Competitive compensation + meaningful equity