Software Engineer, Evaluation Frontend
Cohere
Job Overview
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Job Description
Who are we?
Our mission at Cohere is to scale intelligence to serve humanity. We train and deploy frontier models for developers and enterprises building AI systems for magical experiences like content generation, semantic search, RAG, and agents. We believe 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, 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 an Evaluation Frontend Software Engineer, you will play a key role in helping Cohere make modeling decisions based on experimental outcomes for our large language models (LLMs). Your primary focus will be on building tools to enable easy visualization and analysis of model evaluations, which are stored in a central database. You will work closely with cross-functional teams, including researchers and engineers, to surface the insights necessary for the future development of our models.
This role combines expertise in statistics, data science, frontend development, and data visualization. If any of these topics sound interesting to you, we encourage you to apply.
Please Note: We have offices in London, Paris, Toronto, San Francisco, and New York, but we also embrace being remote-friendly! There are no restrictions on where you can be located for this role.
As a Software Engineer, Evaluation Frontend You Will:
- Design tools and visualizations that enable researchers and engineers to compare and analyze hundreds of model evaluations. This includes both data visualization tools, as well as statistical tools to extract signal from noisy data.
- Develop an understanding of the relative merits and limitations of each of our model evaluations, as well as suggest new facets of model evaluation.
You May Be a Good Fit If You Have:
- Extremely strong software engineering skills.
- Strong statistical skills and experience evaluating scientific experiments related to data collection and model performance.
- Prior experience building front-end visualization systems and dashboards.
- Familiarity with ML systems evaluations.
- 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).
Cohere Employee 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!)
Key skills/competency
- Frontend Development
- Data Visualization
- Statistical Analysis
- Machine Learning Evaluation
- Python Programming
- PyTorch/TensorFlow/JAX
- Software Engineering
- Experimental Design
- Cross-functional Collaboration
- LLM Insights
How to Get Hired at Cohere
- Research Cohere's mission: Understand their focus on scaling AI intelligence and frontier models.
- Highlight visualization skills: Showcase strong experience in data visualization and dashboard development.
- Emphasize ML evaluation expertise: Detail your background in statistical analysis and ML systems evaluation.
- Tailor resume for keywords: Customize your application with terms like "frontend engineering," "LLM evaluation," and "data science."
- Prepare for technical and behavioral interviews: Be ready to discuss complex statistical problems and collaboration experiences.
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