Research Scientist - Machine Learning - Boston, United States
Originally posted 22 April 2026 by the employer.
About the role
This role leads a research direction deriving probabilistic machine learning theory, demonstrating scaling properties, and deploying performant models. The work focuses on training models within Extropic's thermodynamic computing paradigm across hardware, software, physics, and math.
What you'll do
- Collaborate with researchers, residents, engineers, and physicists to derive the theory of new probabilistic models and their learning rules, including energy-based models and diffusion models. - Scale up experimentation infrastructure and optimize over the design space of models. - Implement, visualize, and evaluate new architectures, training algorithms, and benchmarks. - Publish papers, contribute to open source, and communicate design insights to the hardware team. - Create production models for domain experts using customer data.
What you'll need
- Experience in scientific Python and at least one deep learning framework (PyTorch, JAX, TensorFlow, or Keras). - Strong foundations in probability and linear algebra. - Familiarity with deep learning theory and literature, including the theory of over-parameterization and scaling laws. - Publications in ML conferences such as NeurIPS, ICML, ICLR, or CVPR. - Experience training high-performance models and using infrastructure such as Slurm, Ray, and Weights & Biases. - Experience deploying models with infrastructure such as Ray, AWS, and ONNX.
Nice to have
- Experience designing probabilistic graphical models (PGM). - Experience training energy-based models (EBMs) or diffusion models. - Experience with numerical methods in diffeq solvers. - Experience with message passing or training graph neural networks (GNNs). - Strong theoretical background in information geometry or random matrix theory. - Strong grasp of computational Bayesian methods, including MCMC sampling methods and variational inference.
Skills: probabilistic models, deep learning, Python, ML conferences, experimentation infrastructure
This role has been open 133 days — well above the 56-day median for Software Engineering Semiconductor roles.
Software Engineering Semiconductor · Systems Software
|
Open roles in category
342
|
Median days open
56 d
|
Median salary
$147k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Extropic | All employers we track in this specialty (342 roles · 59 employers) |
|---|---|---|
| Open roles in this specialty | 1 | 342 |
| Open roles in the wider Software, Firmware & Systems family | 3 | 6292 · 146 employers |
| Median days open | 133 d | 56 d (+77 d vs this employer) |
| Median salary (USD postings) | — | $147k |
Skills observed across this category: probabilistic models, deep learning, Python, ML conferences, experimentation infrastructure
Who's hiring in this category
- Keysight Technologies · 37 open roles · median 33 d
- NVIDIA · 30 open roles · median 52 d
- Applied Materials · 27 open roles · median 35 d
- Cadence Design Systems · 27 open roles · median 216 d
- Micron Technology · 27 open roles · median 53 d
- KLA Corporation · 26 open roles · median 155 d
How we counted: 342 open Software Engineering Semiconductor (Systems Software) roles from 59 employers tracked in the SemiconductorJobs index, counted 27 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.