---
title: 'Member of ML Technical Staff at Pragmatike'
canonical: 'https://feeny.ai/job/member-of-ml-technical-staff-pragmatike-san-francisco-9jcgzjcf3kv2'
type: 'job'
last_seen: '2026-09-06'
---

# Member of ML Technical Staff at Pragmatike

- **Company:** Pragmatike
- **Location:** San Francisco, CA
- **Compensation:** $200k–$350k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-08-19
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/pragmatike/ad59529e-b796-4f8b-827d-ecb72614d075

## Job description

MEMBER OF TECHNICAL STAFF — LLM RESEARCH & TRAINING

## ABOUT THE ROLE

We are looking for an exceptional Member of Technical Staff specializing in Machine Learning and Large Language Models to join an early-stage AI company building and training state-of-the-art foundation models.

This role sits at the intersection of LLM research, large-scale training infrastructure, post-training, and GPU/kernel optimization.

We are particularly interested in highly motivated researchers and engineers who want to contribute directly to training powerful models — whether their strengths are in theoretical model research, training systems, distributed infrastructure, or low-level performance optimization.

You will work in a small, highly technical team where researchers and engineers collaborate closely and are expected to take ownership across the stack.

## RESPONSIBILITIES

- Research, design, and implement new techniques for training and improving large language models.
- Build and optimize large-scale pre-training and post-training pipelines.
- Improve model training efficiency, throughput, stability, and scalability.
- Work on distributed training across large GPU clusters.
- Design and optimize model-parallel training strategies, including tensor, pipeline, sequence, and data parallelism.
- Optimize GPU workloads using technologies such as CUDA and Triton.
- Improve inference and training kernels when necessary.
- Explore new model architectures, training methodologies, and post-training techniques.
- Run experiments, analyze results, and rapidly iterate on research ideas.
- Collaborate on software/hardware co-design to maximize training throughput.
- Contribute to internal research infrastructure and potentially open-source initiatives.

## WHAT WE'RE LOOKING FOR

## LLM / ML RESEARCH EXPERIENCE

- At least 1+ years of experience in theoretical LLM research or as an ML researcher/engineer at a highly technical AI or technology organization.
- Hands-on experience working with large language models beyond simply consuming existing APIs.
- Experience with one or more of:
- LLM architecture research
- Pre-training
- Post-training
- Reinforcement learning / preference optimization
- Training framework development
- Kernel or inference optimization
- Large-scale distributed training

Experience working on language models at organizations or research environments comparable to OpenAI, Google DeepMind, Mistral AI, Qwen, DeepSeek, Z.ai http://Z.ai, Allen Institute for AI, or leading academic labs is highly relevant.

## LARGE-SCALE TRAINING

Strong understanding of large-scale AI infrastructure and at least some of the following:

- Distributed GPU training
- Model parallelism
- Tensor parallelism
- Pipeline parallelism
- Sequence parallelism
- Data parallelism
- Communication optimization
- Memory optimization
- Training throughput optimization
- Software/hardware co-design

Experience contributing to initiatives such as NanoGPT Speedrun, Marin, or similar open-source model-training projects is a strong plus.

## TECHNICAL SKILLS

Strong proficiency with:

- Python
- PyTorch
- CUDA
- Triton

Experience with JAX is highly valued.

Additional experience with distributed training frameworks, custom kernels, GPU profiling, compiler optimization, or high-performance computing is a plus.

## RESEARCH BACKGROUND

We value candidates who have demonstrated strong technical depth through one or more of:

- ML/AI research during undergraduate, master's, or PhD studies
- Publications or meaningful research contributions
- Open-source ML contributions
- Competitive programming
- Building large-scale ML systems from first principles

A strong undergraduate degree is expected, ideally from a highly selective technical university. Advanced degrees are welcome but not required.

## WHAT MAKES SOMEONE SUCCESSFUL HERE

You are likely to thrive in this role if you:

- Have extremely strong technical fundamentals.
- Are genuinely interested in understanding how modern language models work internally.
- Prefer building and improving models rather than simply applying existing LLMs to business use cases.
- Are comfortable moving between research and engineering.
- Have high energy, intellectual curiosity, and low ego.
- Enjoy working in small, fast-moving teams.
- Are comfortable tackling problems that do not yet have established solutions.
- Can independently turn research ideas into working systems and experiments.

## NICE TO HAVE

- Experience at an early-stage AI startup.
- Contributions to open-source ML frameworks or research projects.
- Experience optimizing GPU kernels or inference engines.
- Experience building training infrastructure from scratch.
- Experience training models across large GPU clusters.
- Strong systems engineering or HPC background.

## NOT A FIT IF

This role is probably not the right fit if your experience is primarily:

- Integrating existing LLM APIs into applications.
- Building RAG or chatbot applications without working on the underlying models.
- Prompt engineering without model training experience.
- Working exclusively in large, highly structured engineering organizations with narrowly defined responsibilities.

## LOCATION

San Francisco, CA

This is an on-site position, 5 days per week, based in San Francisco's Financial District.

## VISA SPONSORSHIP

Visa transfers may be supported, including candidates currently on statuses such as OPT or H-1B, depending on individual circumstances.

## COMPENSATION

Base Salary: $200,000 – $350,000

Plus competitive equity.

Compensation will depend on experience, technical depth, research background, and expected impact.

## HIRING PLAN

We are looking to hire multiple exceptional engineers and researchers for this team.

## About Pragmatike

## Company Overview
- **One-liner**: Pragmatike is a remote tech recruitment platform that connects businesses with vetted software engineers, data specialists, and IT professionals across 60+ countries, promising hires within 48 hours.
- **Entity Type**: Private (bootstrapped/early-stage; no disclosed funding rounds)
- **Headquarters**: Paris, France (with offices in San Francisco, CA, USA and presence in UAE, Armenia, Turkey)
- **Founded**: 2022
- **Founders**: Grégoire Clement (Co-Founder & CEO), Mathias Guigui (COO & Co-Founder)

## Core Business
- **Primary industry**: IT Services and IT Consulting / Talent Recruitment
- **Target customers**: Remote-first companies of all sizes – from startups and scaleups to large enterprises – primarily in SaaS and Fintech, but open to all industries (excluding defense, medical, weaponry)
- **Mission or purpose statement**: “Simplify IT talent recruitment … score top remote developers and tech professionals. Easy peasy!”

## Products & Services
- **Recruitment-as-a-Service**: End-to-end hiring process with human-picked vetting (no AI screening). Clients submit requirements, get matched within 48 hours, and receive a dedicated personal manager for the duration of the engagement.
- **International Payroll & Compliance Management**: Handles contracts, IP protection, and local labor law compliance for remote hires across 100+ countries.
- **Talent Pool Access**: Database of 50K+ candidates globally; specializes in niche technologies (AS400, Erlang, Scala, Elixir, cybersecurity, IoT, ML) as well as standard stacks (React, Node, Python, Swift, etc.).
- **Roles Covered**: Full-stack developers, data engineers, mobile developers, DevOps, product managers, marketing, finance, sales – all fully remote.

## Market Standing
- **Valuation**: Not publicly available
- **Key Metric**: Reports 10,000+ vetted specialists in network; trusted by 50+ brands; currently posting 283 active job openings
- **Notable Investors/Partners**: No investors disclosed; client logos not individually named but described as “unicorns, small businesses, large enterprises”
- **Growth Signals**:
  - Year-over-year job postings growth: **+1079.2%**
  - Operates in 60+ countries
  - Stages talent in 2 offices (Paris, San Francisco) with remote workforce spanning 20+ locations

## Competitive Advantages
- **100% Remote DNA**: The company was built for remote hiring, focusing on international talent – unlike traditional local staffing agencies.
- **Human Vetting, No Fake AI**: Claims a rigorous human selection process (communication, English proficiency, technical test, client validation) rather than automated screening.
- **Speed**: Guaranteed match within 48 hours; trial period offered at €0.
- **Cost Advantage**: 30–50% cheaper than local market rates for freelance developers, with no hidden fees.
- **Flexible, Project-Based Pricing**: No subscriptions or packages; pricing per hour (€31–€59) tailored to client budget.
- **Niche Expertise**: Able to source rare specialists (AS400, Erlang, etc.) often inaccessible via traditional channels.

## Strategic Focus
- **Global Expansion**: Growing presence in EMEA, UAE, and Americas; actively posting jobs across time zones.
- **Quality Over Quantity**: Emphasizes human-curated matches over automated algorithms.
- **SaaS & Fintech Concentration**: Primary verticals, while remaining industry-agnostic for broader reach.
- **Cost Leadership**: Maintaining price advantage to undercut larger competitors like Toptal or Upwork.

## Why Work Here
- **Culture**: Described as a “young startup” that “pampers clients like bees nurturing honey” – high-touch, service-oriented environment.
- **Remote/Hybrid Policy**: Fully remote operations; employees work from physical offices in Paris or San Francisco as needed, but the company is built for remote work.
- **Team**: Small team of ~7 employees (down 25% YoY, likely due to strategic refocus), with HR as the largest department (33%).
- **Growth Opportunity**: Working at a fast-growing platform that tripled job postings in a year offers exposure to global tech talent markets and recruitment ops.
- **Perks**: Not explicitly listed, but flexible, project-based environment with international exposure.

## Sources
1. [pragmatike.com](https://www.pragmatike.com/)
2. [linkedin.com](https://www.linkedin.com/company/pragmatikee)
3. [builtin.com](https://builtin.com/company/pragmatike)
4. [jobs.ashbyhq.com](https://jobs.ashbyhq.com/pragmatike)
5. [pragmatike.com/business](https://www.pragmatike.com/business)

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