Member of Technical Staff, Search

Who We Are

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 intelligent agents. We believe our work is instrumental to the widespread adoption of AI.

We obsess over what we build, with each team member responsible for increasing model capabilities and customer value. We work hard and move fast, always prioritizing our customers.

Cohere is a diverse team of researchers, engineers, designers, and more, all passionate about their craft and among the best in their fields. We believe diverse perspectives are essential for building great products. Join us to shape the future!

Why Join Cohere's Search Team?

We are seeking talented individuals to develop state-of-the-art models for information retrieval within our Search team. This group focuses on training our embedding and reranker models. You will have the opportunity to revolutionize search experiences by contributing to an intelligent, efficient, and precise search system, with ample scope for innovation and productionizing new ideas.

Your work will specifically advance semantic search techniques to improve accuracy and efficiency, involving novel technologies and collaboration with other teams to integrate your contributions into our search infrastructure. We're looking for someone passionate about search with a strong background in information retrieval, experience with diverse technologies, and a history of collaborative teamwork.

Key Responsibilities as a Member of Technical Staff, Search

• Design, train, and continuously improve cutting-edge search models.
• Gather high-quality retrieval datasets and optimize data pipelines for model training and evaluation.
• Work closely with the model serving team to ensure fast and stable inference.
• Collaborate with product teams to develop innovative solutions.
• Engage in research collaborations with partner organizations and academic affiliations, publishing work in top-tier conferences and journals.

Join us at a pivotal moment, shape what we build, adopt a strong ownership mindset, and wear multiple hats!

What You'll Bring

• Proficiency in Python and related ML frameworks such as PyTorch, Tensorflow, TF-Serving, JAX, and XLA/MLIR.
• Familiarity with training and using various information retrieval models.
• Experience leveraging Large Language Models as part of training data or evaluation pipelines.
• Strong communication and problem-solving skills.

Bonus Qualifications

• Experience building training and/or evaluation datasets for practical use cases.
• Proficiency in other programming languages, such as C++ or Golang.
• Experience using large-scale distributed training strategies with GPUs.

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.

Cohere Perks & Culture

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 for 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, with 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

• Python
• PyTorch
• Tensorflow
• Information Retrieval
• Semantic Search
• Large Language Models (LLMs)
• Model Training
• Data Pipelines
• Distributed Training
• AI Research