Description
Compensation
- Canada - Toronto (GTA), Montreal: Base Salary CA$295K – CA$535K • Offers Equity
- Canada: Base Salary CA$250K – CA$460K • Offers Equity
- USA - California, New York and Washington: Base Salary $205K – $380K • Offers Equity
- USA - All Other States: Base Salary $175K – $325K • Offers Equity
Cohere is committed to fair and transparent pay practices. The compensation range listed for this role reflects the expected compensation. Actual compensation offered will be determined by factors such as location, level, job-related knowledge, skills, education, and experience.
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 headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!
Role Overview:
As a Senior Member of Technical Staff specializing in web data for pre-training, you will play a pivotal role in developing the large scale web data pipeline that underpins Cohere’s advanced language models. In this role, you will work extensively with large-scale web corpora, transforming raw, noisy internet data into high-quality training data for pretraining. You will own key components of the data pipeline, including extraction, parsing, deduplication, and filtering. You will also analyze the composition and quality of web data, study its impact on downstream model performance, and collaborate closely with the broader data and evaluation teams to iterate on the training corpus.
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.
Key Responsibilities:
- Maintain large-scale pipelines for processing web corpora.
- Work on filtering and quality-scoring systems to identify high-value web documents.
- Analyze web data composition across domains, languages and time periods.
- Develop and maintain highly-performant deduplication pipelines.
- 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 large-scale web datasets.
- Knowledge of data quality assessment techniques and experimentation with data mixtures.
- A passion for bridging research and engineering to solve complex data-related challenges in AI model training.
Benefits:
- 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.
- 6 weeks of paid vacation (30 working days!)
- Budget for traveling to other offices if you are remote, plus an annual company offsite.
Working Location:
This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.