Logical Intelligence · San Francisco, CA

Salary
Posted
Jul 25, 2026
Location
San Francisco, CA
Last confirmed open
Jul 26, 2026

What this job asks for AI summary

An AI research engineering role focused on developing and improving reasoning algorithms, with a particular emphasis on energy-based modeling (EBM) as an approach that goes beyond standard large language models. Day-to-day work spans pretraining and fine-tuning LLMs, combining them with novel reasoning methods, and building ML pipelines — all in service of formal code verification. Suits candidates with a graduate degree in a relevant field and a research track record, ideally including EBM experience and published work at major ML conferences.

Senior level · Master's required

Must have (5)
Python or C++PyTorch, TensorFlow or JaxLLMsDeep LearningML pipelines
Nice to have (2)
Multi-GPU trainingFormal Verification

“or” means any one of them counts — you don't need all of them.

We read this from the posting text with AI. Skim the description below before ruling yourself out.

How this req sits in the market our data

What won't set you apart
Python88%C++88%Deep Learning40%

Most people in this occupation already list these. Still required — just not what gets you shortlisted.

What the occupation pays Median $122,874 (middle half $87,544–$162,374).

Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.

Why we read it this way (8)

Location is not stated in the posting; the company website (logicalintelligence.com) appears to be a US-based AI startup, so the US-based flag defaults to true, but the actual work location and remote policy are unknown.

Python and C++ are listed together as a paired requirement ('Python/C++'); they are emitted as a single skill with the other as an alternative, reflecting that the JD treats them as interchangeable options for the same high-performance computing requirement.

PyTorch, TensorFlow, and JAX are listed as interchangeable deep learning framework options; PyTorch is used as the primary name with the others as alternatives.

Energy-based Modeling (EBM) is listed in the qualifications block with 'preferable' noted for a Ph.D. focus and EBM research, but the role is explicitly described as being built around EBM and the qualifications section requires 'provable record of Energy-based usage' and 'hands-on with algorithms used to train Energy-based models' — treated as a hard gate.

Multi-node/multi-GPU training and Formal Verification appear under 'Bonus Points' and are marked as preferred.

The degree requirement is M.Sc. or Ph.D. (Ph.D. preferred); M.Sc. is the stated minimum hard gate, so the degree requirement is set to Masters.

No compensation, employment type, or specific work location is disclosed in the posting.

Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): Energy-based Modeling.

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