Member of Technical Staff, MLE (UK/EU) at Cohere

London, England, United Kingdom

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

Prior experience in leading ML teams in applied research and production
Prior experience in setting as well as executing technical direction to build new or to refine existing products
Prior experience in working cross-discipline in matrixed organizations
Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR
Experience using large-scale distributed training and inference
Strong mentorship, communication, and problem-solving skills
A demonstrated passion for applied ML models and products
Bonus: experience working for B2B companies in the ML space

Responsibilities

Work directly with customers to quickly understand their greatest problems and design and implement solutions using Large Language Models
Apply problem-solving ability, creativity, and technical skills to close the last-mile gap in Enterprise AI adoption
Plan and execute large-group projects that carry through from ideation to production
Bring cross-functional alignment across engineering, product and other disciplines
Mentor a distributed team of engineers in subject matter expertise
Identify opportunities and gaps in existing models and strategize what to work on
Work closely with product teams to develop solutions
Engage in collaborations with our partner organizations
Assist our legal teams with preparation of patents on developed IP

Skills

Large Language Models

RAG

Semantic Search

Agents

Machine Learning

Cross-functional Collaboration

Cohere

Provides NLP tools and LLMs via API

About Cohere

Cohere provides advanced Natural Language Processing (NLP) tools and Large Language Models (LLMs) through a user-friendly API. Their services cater to a wide range of clients, including businesses that want to improve their content generation, summarization, and search functions. Cohere's business model focuses on offering scalable and affordable generative AI tools, generating revenue by granting API access to pre-trained models that can handle tasks like text classification, sentiment analysis, and semantic search in multiple languages. The platform is customizable, enabling businesses to create smarter and faster solutions. With multilingual support, Cohere effectively addresses language barriers, making it suitable for international use.

Toronto, CanadaHeadquarters

2019Year Founded

$914.4MTotal Funding

SERIES_DCompany Stage

AI & Machine LearningIndustries

501-1,000Employees

Risks

Competitors like Google and Microsoft may overshadow Cohere with seamless enterprise system integration.

Reliance on Nvidia chips poses risks if supply chain issues arise or strategic focus shifts.

High cost of AI data center could strain financial resources if government funding is delayed.

Differentiation

Cohere's North platform outperforms Microsoft Copilot and Google Vertex AI in enterprise functions.

Rerank 3.5 model processes queries in over 100 languages, enhancing multilingual search capabilities.

Command R7B model excels in RAG, math, and coding, outperforming competitors like Google's Gemma.

Upsides

Cohere's AI data center project positions it as a key player in Canadian AI.

North platform offers secure AI deployment for regulated industries, enhancing privacy-focused enterprise solutions.

Cohere's multilingual support breaks language barriers, expanding its global market reach.

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