Research Engineer

About the Role

Day-to-day, you will be collaborating closely with scientists and other engineers to implement new methods, run large-scale experiments, and help shape the infrastructure that supports the research programs. The work environment is fast-paced and dynamic, with a strong emphasis on curiosity, ownership, and practical impact. Your contributions will be instrumental in advancing machine learning and creating tools that make research more accessible, which in turn will have a significant impact on the widespread adoption of AI.

Cohere Labs brings together researchers and engineers to explore ambitious ideas and turn them into real systems. The focus is on advancing machine learning while expanding access to applied research training and global collaboration. This is achieved through the creation of open, collaborative research spaces where engineers and researchers work side-by-side on ambitious ML problems, and by expanding access to applied research training, helping early-career engineers grow into strong research contributors.

What You Will Do

• Design, implement, and test machine learning models and algorithms to solve complex problems in NLP and AI.
• Collaborate with researchers to identify project goals, design experiments, and analyze results.
• Develop and maintain large-scale datasets for training and testing AI models.
• Work on scaling training pipelines and optimizing model performance.
• Contribute to the development of new methods and tools that make research more accessible.
• Run ablations, analyze results, and iterate quickly on experiment design.
• Implement and optimize deep learning frameworks and model optimization techniques.
• Collaborate closely with cross-functional teams to integrate AI models into larger systems.
• Participate in code reviews to ensure high-quality, maintainable code.
• Help shape the infrastructure that supports research programs and ensure it is scalable and efficient.
• Stay up-to-date with the latest advancements in machine learning, NLP, and deep learning, applying this knowledge to improve current projects and propose new ones.

What We Are Looking For

• A strong engineering background in machine learning, NLP, or related areas, through a Master’s degree, industry experience, or equivalent hands-on work.
• Experience with deep learning frameworks and model optimization techniques, such as PyTorch, distributed training, RLHF, finetuning, and evaluation frameworks.
• Ability to write clean, reliable code and build systems that others can use and extend.
• Comfort with experimenting, running ablations, analyzing results, and iterating quickly.
• Strong collaboration skills, with the ability to work closely with researchers and translate ideas into practical implementations.
• Curiosity and a willingness to learn quickly in a fast-moving research environment.
• Experience with cloud computing platforms and containerization (e.g., Docker).
• Understanding of software development principles, including version control (e.g., Git).
• Excellent communication skills, with the ability to explain complex ideas to both technical and non-technical audiences.
• A passion for building things that are both thoughtful and useful, from new methods and datasets to tools that make research more accessible.

Nice to Have

• Experience working in an open, collaborative research environment.
• Familiarity with agile development methodologies and version control systems.
• Knowledge of additional programming languages beyond Python, such as Java or C++.
• Experience with DevOps practices and tools (e.g., Jenkins, Kubernetes).
• Participation in open-source projects related to machine learning or NLP.
• Prior experience working with large datasets and data processing pipelines.

Benefits and Perks

• The opportunity to work on meaningful problems that have the potential to shape the future of AI.
• Collaborative and dynamic work environment with a team of talented researchers and engineers.
• Professional development opportunities, including access to cutting-edge research and technologies.
• Flexible working arrangements and remote work options.
• Competitive compensation package, including equity for eligible roles.
• Comprehensive health insurance and wellness programs.
• Generous PTO policy to ensure a healthy work-life balance.
• Access to the latest tools and technologies to support your work.
• Opportunities for career growth and advancement within the company.
• A culture that values diversity, inclusivity, and equal opportunities for all employees.

About Cohere

• Ensure your resume and cover letter highlight specific experiences with machine learning, NLP, and deep learning.
• Prepare examples of projects you’ve worked on, especially those involving large-scale datasets and model optimization.
• Familiarize yourself with Cohere’s mission and research focus to understand how your skills can contribute to their goals.
• Practice explaining complex technical concepts in simple terms, as this will be valuable in your collaborations with researchers.
• Consider creating a portfolio or GitHub repository showcasing your coding projects and contributions to open-source initiatives.
• Be prepared to discuss your approach to problem-solving, experimentation, and iteration in a fast-paced research environment.
• Don’t hesitate to ask about the company culture, opportunities for growth, and how your role contributes to the overall mission of Cohere.