About the job
Who We Are:
At Cohere, our mission is to harness the power of intelligence for the betterment of humanity. We are at the forefront of developing and deploying cutting-edge models for developers and enterprises, enabling them to create transformative AI experiences like content generation, semantic search, retrieval-augmented generation (RAG), and intelligent agents. We firmly believe that our contributions are vital for the widespread integration of AI technologies.
Our passion for innovation drives us. Each team member is accountable for enhancing our models' capabilities and delivering exceptional value to our customers. We thrive in a fast-paced environment, committed to excellence and customer satisfaction.
Cohere comprises a diverse team of researchers, engineers, and designers, each a leader in their respective fields. We believe that diverse perspectives are essential to building outstanding products.
Join our journey and help shape the future of AI!
Why This Role Matters:
As a Machine Learning Engineer focused on synthetic data, you will be instrumental in developing the synthetic data pipeline that supports Cohere's advanced language models. Your role will involve overseeing the entire lifecycle of synthetic data, which includes maintaining and optimizing the synthetic data pipeline, performing data analysis and generation, and conducting data ablation and model evaluations to assess data quality. You will work with diverse datasets, transforming them through generative models to enhance token efficiency and model performance. By merging research with engineering, you will connect raw data to state-of-the-art AI models, directly impacting critical training metrics such as throughput and accelerator utilization.
Your contributions will be pivotal to our mission of providing efficient and reliable language understanding and generation capabilities, fostering innovation in natural language processing. If you have a passion for transforming data into the backbone of AI systems, this role presents a unique opportunity to make a significant impact.
Please note: We have offices in London, Paris, Toronto, San Francisco, and New York, and we are proud to be a remote-friendly company! There are no location restrictions for this role within the EST and EU time zones.
Your Responsibilities:
Design and implement scalable inference pipelines that operate efficiently on large GPU clusters.
Conduct data ablation studies to evaluate data quality and experiment with diverse data mixtures to enhance model performance.
Collaborate with cross-functional teams to integrate synthetic data solutions into existing AI frameworks.
Analyze and optimize data generation processes to support various AI applications.
