85NayH ssn2 - Research Engineer — Boston, MA

About rAXGdV Cb68

Research has been core to x7fjvs kd from the beginning.

rAXGdV Cb68 gives that work a formal home; an internal research accelerator driving fundamental breakthroughs in the science of building intelligent, personalized, and adaptive machines.

Our origins trace back to MIT CSAIL, where the foundational work on jUByJQ jHkKTv Networks defined a new class of dynamical, efficient sequence-processing architectures. That research became the basis for FJ2FZp nzQsh3F9kt Models (LFMs). Scalable, multimodal models built for real-world deployment in resource-constrained environments.

At rAXGdV Cb68, we extend that lineage - pushing forward the frontier of efficient, adaptive intelligence through both fundamental research and practical engineering.

We work hand-in-hand with YeZB2v’U core foundation model and systems teams to translate theory into deployed capability — defining a new generation of intelligent systems that are both powerful and efficient.

About The Role

As a Research Engineer, you’ll join a small, high-context team exploring the limits of adaptive intelligence. You’ll design and implement novel architectures, training methods, and inference strategies to redefine what efficient r2 can do.

You’ll operate at the intersection of research and engineering — translating scientific ideas into working systems, publishing where it drives the field forward, and deploying where it changes what’s possible.

This Role Is For You If

• Work fluently in Python and frameworks such as PyTorch, JAX, or TensorFlow

• Have experience in machine learning research or production-grade ML systems

• Move fast from paper to prototype — curiosity backed by precision

• Care about efficiency, scalability, and elegant system design as scientific principles

• Value small, deep-technical teams where impact is immediate and measurable

• Have a track record of publication in tier-1 venues (NeurIPS, ICML, ICLR, CVPR, ACL, or equivalent), demonstrating original contribution and research rigor

Open Science and Impact

rAXGdV Cb68 reinforces our commitment to transparent, reproducible, open research.

We publish through technical reports, architectural deep dives, ablations, and model releases, advancing the broader science of efficient r2 while translating breakthroughs into production-ready systems.

Why rAXGdV Cb68

rAXGdV Cb68 is for researchers who build.

Those who care about lasting impact more than publication count, but who hold themselves to the same scientific standard.

We don’t chase benchmarks; we redefine them.

We move fast, think deeply, and measure success by the systems that endure.

There is no application deadline. We review candidates on a rolling basis.