Member of Technical Staff, Next Generation Agents

London, England, United Kingdom

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Not SpecifiedCompensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, AI & Machine Learning, Research & DevelopmentIndustries

Requirements

Candidates should possess strong software engineering skills and proficiency in Python, along with experience using ML-related code such as PyTorch and NumPy. They should also have experience with Large Language Models (LLMs) and agentic frameworks, as well as familiarity with post-training LLMs including SFT, PEFT, and RL*. Experience building synthetic data generation pipelines is beneficial.

Responsibilities

As a Member of Technical Staff, the individual will design and develop novel agentic solutions, improve upon state-of-the-art performance on agentic tasks, research the next-generation of online learning-from-experience self-improvement, and collaborate with partner teams to enhance the performance of agentic systems. They will also contribute to developing data-generation techniques for post-training LLMs.

Skills

Deep learning

Reinforcement learning

Continual learning

Memory models

Data-generation techniques

Model training

Empirical research

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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