[Remote] Member of Technical Staff, Synthetic Data at Cohere

Toronto, Ontario, Canada

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Machine LearningIndustries

Requirements

Strong software engineering skills, with proficiency in Python and experience building data pipelines
Familiarity with data processing frameworks such as Apache Spark, Apache Beam, Pandas, or similar tools
Experience working with LLMs through work projects, open-source contributions or personal experimentation
Familiarity with LLM inference frameworks such as vLLM and TensorRT
Experience working with large-scale datasets, including web data, code data, and multilingual corpora
A passion for bridging research and engineering to solve complex data-related challenges in AI model training
Bonus: paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP)

Responsibilities

Design and build scalable inference pipelines that run on large GPU clusters
Conduct data ablations to assess data quality and experiment with data mixtures to enhance model performance
Research and implement innovative synthetic data curation methods, leveraging Cohere’s infrastructure to drive advancements in natural language processing
Collaborate with cross-functional teams, including researchers and engineers, to ensure data pipelines meet the demands of cutting-edge language models
End-to-end management of synthetic data, including maintaining and optimizing the synthetic data pipeline, data analysis and generation, and conducting data ablations and model evaluation to gauge data quality
Work with diverse web data and code data and transform them using generative models to improve token efficiency and model quality
Bridge the gap between raw data and cutting-edge AI models, contributing to improvements in critical training metrics like throughput and accelerator utilization

Skills

Key technologies and capabilities for this role

Machine LearningSynthetic DataData PipelineGenerative ModelsData AnalysisModel EvaluationNatural Language ProcessingRAGToken EfficiencyAccelerator Utilization

Questions & Answers

Common questions about this position

Is this position remote-friendly?

Yes, the position is fully remote with no restrictions on location as long as you are between EST and EU time zones. The company has offices in London, Paris, Toronto, San Francisco, and New York but embraces remote work.

What skills are required for this role?

Strong software engineering skills with proficiency in Python and experience building data pipelines are required. Familiarity with data processing is also needed.

What does the company culture at Cohere look like?

Cohere is a team of top researchers, engineers, and designers who obsess over their work, move fast, and value diverse perspectives to build great products. They emphasize hard work to best serve customers and scale intelligence.

What is the salary or compensation for this role?

This information is not specified in the job description.

What makes a strong candidate for this position?

Candidates with strong software engineering skills, Python proficiency, experience building data pipelines, and familiarity with data processing will be a good fit. Passion for synthetic data, machine learning, and natural language processing, along with the ability to design scalable pipelines and collaborate cross-functionally, are key.

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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