Member of Technical Staff, Pre-Training Data Engineer

Toronto, Ontario, Canada

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Not SpecifiedCompensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, AI & Machine Learning, Data Engineering, Natural Language ProcessingIndustries

Requirements

Candidates should possess strong software engineering skills, with proficiency in Python and experience building data pipelines, along with familiarity with data processing frameworks such as Apache Spark, Apache Beam, Pandas, or similar tools. Experience working with large-scale datasets, including web data, code data, and multilingual corpora is required, as well as knowledge of data quality assessment techniques and experimentation with data mixtures.

Responsibilities

As a Pre-Training Data Engineer, you will design and build scalable data pipelines to ingest, clean, filter, and optimize diverse datasets, conduct data ablations to assess data quality and experiment with data mixtures to enhance model performance, develop robust data modeling techniques to ensure datasets are structured and formatted for optimal training efficiency, research and implement innovative data curation methods, and collaborate with cross-functional teams to meet the demands of cutting-edge language models.

Skills

Data Infrastructure

Data Ingestion

Data Cleaning

Data Filtering

Data Optimization

Data Modeling

Pipeline Development

Data Ablation

Data Mixture Experimentation

Data Quality Assurance

Multilingual Data

Synthetic Data

Scalable Data Processing

Research and Engineering

Model Performance Optimization

Throughput

Accelerator Utilization

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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