Member of Technical Staff, Agent Code

Cohere

New York (NY)

Hybrid

USD 180,000 - 240,000

Full time

14 days+

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Benefits offered by this job

Weekly lunch stipend
Health and dental benefits
RRSP matching & Pension
Parental Leave top-up
Enrichment benefits
Paid vacation
Office travel budget & offsite

Job summary

Cohere is seeking a senior member for the Agent Code team to push the boundaries of code LLMs and autonomous agents. This hands-on, research-driven role focuses on developing production-ready systems and collaborating with engineers and researchers to solve complex tasks with minimal human oversight.

You will stay current with the latest research, design scalable training and deployment pipelines, and lead experiments on our compute infrastructure across global time zones, contributing to

Qualifications

  • PhD in CS/ML with top-tier publications.
  • Deep expertise in code LLMs and agent systems.
  • Hands-on with frontier LLMs for code generation.

Responsibilities

  • Stay up-to-date with the latest research in code LLMs, agents, and related fields.
  • Design and implement scalable training and deployment for code models and agent frameworks.
  • Lead experiments on frontier compute infrastructure and benchmarks.
  • Collaborate with research and engineering teams to productionize solutions.

Skills

Code LLMs
Agent systems
Python
PyTorch
TensorFlow
Distributed systems
Cloud infrastructure
Open-ended problems
Proactive mindset

Education

PhD in CS/ML

Job description

Why this role?

Code‑generating LLMs and autonomous agents are revolutionizing how software is built and tasks are automated. At Cohere, we’re pushing the boundaries of what’s possible with these technologies for enterprises, and we’re looking for a senior member for the Agent Code team. You’ll be at the forefront of research and engineering, driving the development of cutting‑edge code LLMs and agent systems that can interact with the digital world to solve complex tasks with minimal human oversight.

This role is hands‑on and research‑driven. You’ll dive into the latest literature on code LLMs and agents, experiment with frontier models, and collaborate with a team of talented engineers and researchers to build scalable, production‑ready solutions. At Cohere, we blend engineering and research seamlessly—everyone contributes to both, depending on their interests and organizational needs.

Note: We have offices in London, Toronto, New York and San Francisco, but we’re also remote‑friendly! This team operates primarily between ET to CET time zones, so we’re seeking candidates in locations that align with these hours for effective collaboration.

As a Member of Technical Staff on the Agent Code team, you will:

  • Stay up‑to‑date with the latest research in code LLMs, agents, and related fields, implementing novel ideas into our systems.
  • Design and implement scalable strategies to train code models, and deploy agent frameworks for inference and sampling. You will be collaborating with the pretraining team, create SFT trajectories and work on existing and new RL algorithms.
  • Hillclimb on existing benchmarks and design new ones that reflect the needs of our enterprise users.
  • Lead experiments on our state‑of‑the‑art compute infrastructure, pushing the boundaries of what’s possible with frontier LLMs.

You may be a good fit if you have:

  • A PhD in Computer Science, Machine Learning, or a related field, with publications in top‑tier venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP).
  • Deep expertise in code LLMs and agent systems, with a strong understanding of the latest research and trends. We are looking for people who not only have worked with code models, but have actively contributed to their development.
  • Hands‑on experience with frontier LLMs and their applications in code generation or automation.
  • Strong software engineering skills, with proficiency in Python and PyTorch, TensorFlow, or similar frameworks.
  • Experience with distributed systems, cloud infrastructure, and scalable architectures.
  • A proactive, self‑motivated mindset, with a passion for solving ambitious, open‑ended problems.

What We Offer:

  • The opportunity to work on cutting‑edge problems at the intersection of AI, code generation, and autonomous agents.
  • Access to world‑class compute resources, data, and a collaborative team of researchers and engineers.
  • A remote‑friendly, flexible work environment with a focus on impact and innovation.
  • Competitive compensation and benefits, including equity in a fast‑growing AI company.
Full‑Time Employees at Cohere enjoy these Perks:
  • A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
  • Full health and dental benefits, including a separate budget for mental health.
  • RRSP matching, 401K, Pension Scheme.
  • 100% Parental Leave top‑up for up to 6 months, for either parent.
  • Annual enrichment benefits:
    • Arts & culture, fitness/wellness, quality time, and a workspace improvement credit.
    • Education & learning stipend for conferences, courses, and coaching.
  • 6 weeks of paid vacation (30 working days)
  • Budget for traveling to other offices if you are remote, plus an annual company offsite.
How and Where We Work:
  • Cohere is remote‑friendly. We have offices in Toronto, San Francisco, New York City, London, Paris, Montreal, and more coming soon.
  • For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
  • For those not near an office: a co‑working benefit so you can work alongside others in your city.
  • Everyone receives a $500 home office stipend to set up your workspace properly.

We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.

We may use AI‑enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.

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