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Full-Time

Systems Research Engineer

GPU Programming

Confirmed live in the last 24 hours

Together AI

Together AI

51-200 employees

Enterprise Software
AI & Machine Learning

Compensation Overview

$160k - $230kAnnually

+ Equity + Benefits

Mid, Senior

San Francisco, CA, USA

Category
Applied Machine Learning
Deep Learning
AI Research
AI & Machine Learning
Required Skills
CUDA
Requirements
  • Strong background in GPU programming and parallel computing, such as CUDA and/or Triton.
  • Knowledge of ML/AI applications and models
  • Knowledge of performance profiling and optimization tools for GPU programming
  • Excellent problem-solving and analytical skills
  • Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or equivalent practical experiences
Responsibilities
  • Optimize and fine-tune GPU code to achieve better performance and scalability
  • Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems
  • Stay up-to-date with the latest advancements in GPU programming techniques and technologies

Company Stage

Series A

Total Funding

$222.3M

Headquarters

Menlo Park, California

Founded

N/A

Growth & Insights
Headcount

6 month growth

74%

1 year growth

135%

2 year growth

683%
Simplify Jobs

Simplify's Take

What believers are saying

  • The $106M funding round led by Salesforce Ventures provides significant capital for growth and innovation.
  • Hiring top talent, such as the head of sales operations from Coinbase, strengthens the company's leadership team.
  • The release of the biological foundational model Evo opens new avenues in biotech, potentially revolutionizing DNA, RNA, and protein sequence analysis.

What critics are saying

  • The competitive landscape in AI hardware optimization is intense, with new entrants like Groq posing potential threats.
  • Dependence on Nvidia's GPUs could be a vulnerability if supply chain issues or technological shifts occur.

What makes Together AI unique

  • Together AI's collaboration with top-tier institutions like Meta, Nvidia, and Princeton University on FlashAttention-3 showcases its cutting-edge research capabilities.
  • The company's focus on optimizing LLMs for Nvidia Hopper GPUs positions it uniquely in the AI hardware optimization space.
  • Together AI's valuation of $1.25 billion and backing from industry giants like Salesforce Ventures and Nvidia highlight its strong market position and investor confidence.