Senior Member of Technical Staff, Synthetic Data

Rozgoo; United States; Remote; USD 140.000 - 230.000; Vollzeit

Benefits dieser Stelle

Health and dental benefits

Weekly lunch stipend

RRSP matching

Parental leave

Remote-friendly offices

Zusammenfassung

Cohere is seeking a Senior Machine Learning Engineer focused on synthetic data to own the end-to-end data pipeline for advanced language models.

You will work on data ablations, data generation, and model evaluation to boost throughput and model quality, leveraging its diverse web and code data and cutting-edge generative techniques.

Qualifikationen

• Strong software engineering skills with Python and data pipelines.
• Experience with data processing frameworks (Spark/Beam/Pandas).
• Experience with LLMs through projects or open-source work.
• Familiarity with LLM inference frameworks (vLLM, TensorRT).
• Experience with large-scale web and code data and multilingual corpora.
• Passion for bridging research and engineering in AI model training.

Aufgaben

• Design and build scalable inference pipelines for large GPU clusters.
• Conduct data ablations and experiments with data mixtures to improve model performance.
• Research synthetic data curation methods using Cohere's infrastructure.
• Collaborate with researchers and engineers to meet model training needs.

Kenntnisse

Python

Data pipelines

Spark / Beam

Pandas

LLMs

TensorRT

Large-scale datasets

Tools

Apache Spark

Apache Beam

Pandas

vLLM

TensorRT

Jobbeschreibung

Who are we?

Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We're training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Join us!

Why this role?

As a Senior Machine Learning Engineer specializing in synthetic data, you will play a pivotal role in developing the synthetic data pipeline that is crucial to Cohere's advanced language models. Your responsibilities will encompass the end-to-end management of synthetic data, including maintaining and optimizing the synthetic data pipeline, data analysis and generation, as well as conducting data ablations and model evaluation to gauge data quality. You will work with diverse web data and code data and transform them using generative models to improve token efficiency and model quality. By combining research and engineering, you will bridge the gap between raw data and cutting-edge AI models, directly contributing to improvements in critical training metrics like throughput and accelerator utilization. Your work will be essential to Cohere's mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a meaningful impact. Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friendly! There are no restrictions on where you can be located for this role between EST and EU

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.

Qualifications

• 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).

We value and celebrate diversity and strike 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.

We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.

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
• A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
• Full health and dental benefits, including a separate budget for mental health.
• RRSP matching, 401K, Pension Scheme.
• 100% Parental Leave top-up for up to 6 months, for either parent.
• Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit.
• Education & learning stipend for conferences, courses, and coaching.
• Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend 6 weeks of paid vacatio