Senior Member of Technical Staff, Safety and Security for Agents

Cohere; New York (NY); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Inclusive work culture

Work with cutting-edge AI technology

Weekly lunch stipend and snacks

Full health and dental benefits

Parental leave top-up for 6 months

Personal enrichment benefits

Remote flexibility and co-working stipend

6 weeks of vacation

Job summary

A leading AI technology company in New York seeks a Member of Technical Staff focused on developing safer and more trustworthy Large Language Models (LLMs). The role requires strong statistical and software engineering skills, with responsibilities including data generation and collaboration with cross-functional teams. Candidates should have hands-on experience training LLMs and be proficient in Python and related ML frameworks. The company values diversity and offers a flexible work environment with competitive benefits.

Qualifications

• Proven statistical skills in evaluating scientific experiments.
• Strong software engineering capabilities.
• Experience managing data collection with human annotators.
• Skilled in dataset quality evaluation for ML training.
• Hands-on training of large language models on distributed systems.
• Expertise in enhancing ML system robustness.

Responsibilities

• Develop better and safer Large Language Models (LLMs).
• Collaborate with machine learning and data annotation teams.
• Tackle new scientific problems in model safety.

Skills

Strong statistical skills

Strong software engineering skills

Experience with data collection tasks

Experience analyzing datasets

Hands-on experience training large language models

Familiarity with ML systems

Proficiency in Python

Excellent communication skills

Publications in top-tier venues

Tools

Python

PyTorch

TensorFlow

JAX

Job description

Who are we?

Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.

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. We like to work hard and move fast to do what’s best for our customers.

Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.

Join us on our mission and shape the future!

Why this role?

As a Member of Technical Staff in the Safety for Agents team, you will make a meaningful impact on the development of better, fairer, more trustworthy, and more secure Large Language Models (LLMs). Your primary focus will be on data generation, post‑training algorithms, and evaluation methods to ensure Safety in the next generation of models that can access external resources and take actions in the world. You will work closely with other cross‑functional machine learning teams and data annotation teams, and will also collaborate with product and policy teams.

This role combines expertise in machine learning, ethical and responsible AI, experimental design, and data generation and management.

It will require curiosity to tackle totally new scientific problems, engineering skills to implement the pieces we need to test solutions to these, and a desire to dive into messy data and results. You will be on a small team with a lot of autonomy and decision‑making power, responsible for making the next generation of LLMs better for society as a whole.

Please note: The existing team works in offices in London, Edinburgh, Paris, Toronto, and New York, but we also embrace being remote‑friendly! For this role you need to have ~50% working day overlap with UK/EU timezone (e.g. US East is fine) but there are otherwise no restrictions on where you can be located for this role.

You May Be a Good Fit If You Have

• Strong statistical skills and experience evaluating scientific experiments related to data collection and model performance.
• Extremely strong software engineering skills.
• Strong expertise in designing and conducting data collection tasks, including working with human annotators.
• Experience analyzing datasets with respect to their quality, biases, and suitability for training ML models.
• Hands‑on experience training large language models (LLMs) on distributed training infrastructures.
• Familiarity with evaluating and improving the generalizability and robustness of ML systems.
• Proficiency in programming languages such as Python and ML frameworks (e.g., PyTorch, TensorFlow, JAX).
• Excellent communication skills to collaborate effectively with cross‑functional teams and present findings.
• One or more papers at top‑tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).

If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply!

We value and celebrate diversity and 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.

Full-Time Employees At Cohere Enjoy These Perks

• 🤝 An open and inclusive culture and work environment
• 🧑💻 Work closely with a team on the cutting edge of AI research
• 🍽 Weekly lunch stipend, in‑office lunches & snacks
• 🦷 Full health and dental benefits, including a separate budget to take care of your mental health
• 🐣 100% Parental Leave top‑up for up to 6 months
• 🎨 Personal enrichment benefits towards arts and culture, fitness and well‑being, quality time, and workspace improvement
• 🏙 Remote‑flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co‑working stipend
• ✈️ 6 weeks of vacation (30 working days!)