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Join us on our mission and shape the future! 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.
Job Responsibility:
Design, train and improve upon cutting-edge models
Help develop new techniques to train and serve models safer, better, and faster
Train extremely large-scale models on massive datasets
Explore continual and active learning strategies for streaming data
Learn from experienced senior machine learning technical staff
Work closely with product teams to develop solutions
Ship state of the art models to production
Design and implement novel research ideas
Build elegant training/deployment pipelines
Requirements:
Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR
Experience using large-scale distributed training strategies
Familiarity with autoregressive sequence models, such as Transformers
Strong communication and problem-solving skills
A demonstrated passion for applied NLP models and products
Student currently enrolled in a post-secondary program
Available for a full-time 3-6 month internship, co-op, or research work term
Nice to have:
Experience writing kernels for GPUs using CUDA
Experience training on TPUs
Papers at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP)
What we offer:
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 up to 6 months
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