Member of Technical Staff - Post-training (Data Infrastructure)

Cohere; Toronto; Remote; CAD 295,000 - 535,000; Full time

Benefits offered by this job

Lunch stipend

Health and dental benefits

RRSP matching / pension

100% Parental Leave top-up

Enrichment benefits

Education stipend

Paid vacation (6 weeks)

Office/travel and home office stipend

Job summary

Cohere is a leading security-first enterprise AI company building foundation AI models and end-to-end products. We are hiring for a role that builds and owns pipelines for post-training data used to train large language models.

You will collaborate with researchers and annotation teams to iterate on data as models evolve. The role focuses on SFT, RL data, and synthetic/human-annotated data; remote-friendly with offices worldwide.

Qualifications

• Strong software engineering skills.
• Experience designing and building large-scale data pipelines for ML, ideally for LLM post-training.
• Track record of running distributed data processing and model inference at scale.
• Good understanding of post-training methods (SFT, RLHF, DPO) and how data shapes model behaviour.
• Excellent communication skills.

Responsibilities

• Build and maintain data pipelines for SFT, preference, and RL post-training data.
• Own dataset quality, versioning, and reproducibility.
• Turn research data recipes into production-grade, reusable components.
• Scale model inference for data generation and model-based grading.
• Design data formats and schemas to keep datasets consistent and efficient to train on.
• Collaborate with researchers and engineers to keep data pipelines aligned with model needs.

Skills

Software engineering

Designing data pipelines

Distributed data processing

Post-training methods (SFT RLHF DPO)

Communication

Job description

Who are we?

Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.

Who are we?

Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.

We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.

We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.

We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!

Role Overview

As a Member of Technical Staff in Post-Training Data Infrastructure, you will build and own the pipelines that produce the post-training data for our large language models (LLMs), from SFT and RL data to synthetic and human-annotated data. You will work closely with researchers and annotation teams so they can iterate on data as quickly as they iterate on models.

Key Responsibilities

• Build and maintain data pipelines for SFT, preference, and RL post-training data.
• Own dataset quality, versioning, and reproducibility.
• Turn research data recipes into production-grade, reusable components.
• Scale model inference for data generation and model-based grading.
• Design data formats and schemas that keep post-training datasets consistent and efficient to train on.
• Collaborate with researchers and engineers to make sure data pipelines keep pace with the needs of cutting-edge language models.

Qualifications

• Strong software engineering skills.
• Experience designing and building large-scale data pipelines for machine learning, ideally for LLM post-training.
• Track record of running distributed data processing and model inference at scale.
• Good understanding of post-training methods (e.g., SFT, RLHF, DPO) and how data shapes model behaviour.
• Excellent communication skills.

This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, we value diverse backgrounds and perspectives at Cohere.

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, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening 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.

Compensation Range: CA$295K - CA$535K