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- Tasks: Design and build scalable data pipelines for diverse datasets to enhance AI model performance.
- Company: Join Cohere, a leading tech company shaping the future of AI.
- Benefits: Enjoy competitive salary, health benefits, remote work options, and generous vacation time.
- Why this job: Make a real impact in AI by transforming data into powerful language models.
- Qualifications: Strong Python skills and experience with data processing frameworks are essential.
- Other info: Collaborative environment with a focus on diversity and inclusion.
The predicted salary is between 36000 - 60000 £ per year.
Member of Technical Staff, Pre-Training Data
Who are we?
Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.
Who are we?
Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.
Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.
Join us on our mission and shape the future!
Why this role?
As a Machine Learning Engineer specializing in pretraining data, you will play a pivotal role in developing the data pipeline that underpins Cohere’s advanced language models. Your responsibilities will encompass the end-to-end management of training data, including ingestion, cleaning, filtering, and optimization, as well as data modeling to ensure datasets are structured and formatted for optimal model performance. You will work with diverse data sources—such as web data, code data, multilingual corpora, and synthetic data—to ensure their quality, diversity, and reliability.
In this role, you will design and implement scalable, robust pipelines for data processing, conduct data ablations to evaluate quality, and experiment with data mixtures to enhance model performance. 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.
As a Machine Learning Engineer (Pre-Training Data), You Will
- Design and build scalable data pipelines to ingest, clean, filter, and optimize diverse datasets, including web data, code data, multilingual corpora, and synthetic data.
- 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, 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.
You May Be a Good Fit If You Have
- 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 datasets, including web data, code data, and multilingual corpora.
- 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.
Bonus: paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).
If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! If you want to work really hard on a glorious mission with teammates that want the same thing, Cohere is the place for you.
We value and celebrate diversity and strive 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.
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
Weekly lunch stipend, in-office lunches & snacks
Full health and dental benefits, including a separate budget to take care of your mental health
100% Parental Leave top-up for 6 months for employees based in Canada, the US, and the UK
Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
6 weeks of vacation
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Member of Technical Staff, Pre-Training Data employer: Cohere
Contact Detail:
Cohere Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Member of Technical Staff, Pre-Training Data
✨Tip Number 1
Network like a pro! Reach out to current employees at Cohere on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for the interview process. Personal connections can give you an edge!
✨Tip Number 2
Prepare for technical interviews by brushing up on your Python skills and data pipeline knowledge. Practice coding challenges and be ready to discuss your past projects, especially those involving large datasets and machine learning.
✨Tip Number 3
Show your passion for AI! During interviews, share your thoughts on recent advancements in natural language processing and how they relate to Cohere's mission. This will demonstrate your enthusiasm and alignment with their goals.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Cohere team.
We think you need these skills to ace Member of Technical Staff, Pre-Training Data
Some tips for your application 🫡
Show Your Passion: Let us see your enthusiasm for AI and data! In your application, share why you're excited about the role and how it aligns with our mission to scale intelligence for humanity.
Tailor Your CV: Make sure your CV highlights relevant experience, especially in building data pipelines and working with large datasets. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Use your cover letter to tell us your story. Explain how your background and experiences make you a great fit for the Member of Technical Staff role and how you can contribute to our team.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role you’re interested in!
How to prepare for a job interview at Cohere
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of datasets mentioned in the job description, like web data and multilingual corpora. Be ready to discuss your experience with data cleaning, filtering, and optimization, as these are crucial for the role.
✨Showcase Your Technical Skills
Brush up on your Python skills and be prepared to talk about any data processing frameworks you've used, such as Apache Spark or Pandas. You might even want to bring examples of projects where you built data pipelines to demonstrate your expertise.
✨Prepare for Problem-Solving Questions
Expect questions that assess your ability to tackle complex data-related challenges. Think of specific instances where you had to experiment with data mixtures or conduct data ablations, and be ready to explain your thought process and outcomes.
✨Emphasise Collaboration
Since the role involves working with cross-functional teams, highlight your teamwork experiences. Share examples of how you’ve collaborated with researchers and engineers in the past to ensure data pipelines meet project demands.
