Job details

Member of Technical Staff, Modeling

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Boson AI is an early-stage startup building large language tools for interaction and entertainment. Our founders, Alex Smola, Mu Li, and a team of Deep Learning, Optimization, NLP, AutoML and Statistics scientists and engineers are working on high quality generative AI models for language and beyond.

We are seeking research scientists and engineers to join our team full-time in our Santa Clara office. As part of your role, you will work on modeling and training LLMs, understanding and interpreting model behavior and aligning models to human values. The ideal candidate will possess a strong background in machine learning, and have motivations for developing state-of-the-art models towards AGI.

Responsibilities

Design and verify novel model architectures and training objectives.
Investigate novel model alignment algorithms.
Write efficient and clean code for ML training.
Conduct large-scale experiments to verify the modeling choices and identify improvement areas.

Experience

Summarize results and clearly communicate the motivations and observations in your work
Proficiency in at least one deep learning framework, such as PyTorch.
Participation in at least one research project related to LLM or multimodal models, e.g. experience in training or fine-tuning them.
Experience in alignment research
Experience in large-scale distributed model training
Experience in writing GPU kernels in CUDA

Qualifications

PhD or Master's degree with solid scientific contributions
Active GitHub repository
Active scientific track record
Excellent problem-solving skills

$150,000 - $600,000 a year

Total compensations includes base pay, equity, and benefits. We have a 401k plan, HSA, FSA, free food (even dried mangoes).

Average salary estimate

$375000 / YEARLY (est.)

min

max

$150000K

$600000K

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What You Should Know About Member of Technical Staff, Modeling, Boson AI

Join Boson AI as a Member of Technical Staff in Toronto, where you'll be at the forefront of developing cutting-edge large language models and generative AI tools designed for interaction and entertainment. At Boson AI, we pride ourselves on our collaborative environment, led by visionary founders Alex Smola and Mu Li, alongside a talented team of scientists and engineers specializing in Deep Learning, NLP, AutoML, and Statistics. Your main mission will be to design, model, and train large language models while ensuring their behavior aligns with human values. This is a fantastic opportunity if you're passionate about advancing machine learning technologies toward Artificial General Intelligence (AGI). You'll dive into creating novel model architectures, experimenting with alignment algorithms, and writing clean, efficient code for machine learning training. We value innovative thinkers who can summarize and communicate their findings effectively. A solid foundation in machine learning, especially within deep learning frameworks like PyTorch, is crucial. If you have a research background in LLMs or multimodal models, along with hands-on experience in large-scale distributed model training and creating GPU kernels in CUDA, we encourage you to apply. Remember, we also offer an attractive compensation package that reflects your skills and contributions, ranging from $150,000 to $600,000 a year, inclusive of base pay, equity, and benefits. Our perks include a well-stocked kitchen with snacks like dried mangoes and a comprehensive benefits plan including a 401k and HSA.

Frequently Asked Questions (FAQs) for Member of Technical Staff, Modeling Role at Boson AI

What are the primary responsibilities of a Member of Technical Staff at Boson AI?

As a Member of Technical Staff at Boson AI, your key responsibilities will include designing and verifying innovative model architectures and training objectives, investigating alignment algorithms, and conducting large-scale experiments to refine model performance. You'll also be responsible for writing clean and efficient code for ML training and sharing your insights via summaries of your results.