Efficiency Research Engineer at Adaption
Date: 6 hours ago
City: Toronto, ON
Contract type: Full time
Remote
About Us
We believe the future is adaptable, and not one-size-fits-all. We will lead in real-time efficient adaptation that combines algorithm with innovative interface design. Our global team—based in SF and beyond—brings together top talent in AI innovation. Backed by world-class investors, we're building Adaptable Intelligence.
Our Research Values
We are extremely driven and focused on one goal: building highly efficient, adaptable intelligence. We work as a single team, and place focus on a few key bets at a time. We are not driven by the goal of maximizing number of papers. We only publish when our work has a real world impact. If a simple method works well, we prioritize over a more complex and less performant method even if it is not as elegant. Our choices are always motivated by rigor and experimental success. We share back insights to the wider ecosystem to drive wider progress in the direction of continuous learning and highly efficient adaptable intelligence.
The Role
We are obsessed with efficiency— allowing for real-time evolution of AI depends on making adaptable intelligence extremely efficient. We co-design our algorithms with hardware requirements and serving in mind. We explore new research and algorithms within severe compute budgets. These budgets force us to innovate and collaborate across software, hardware, and algorithm.
This role is a part of the founding team, shaping both the research agenda and the product direction. You’ll collaborate with world-class peers and work at the cutting edge of AI efficiency research, where constraints drive creativity. You will contribute to building a company where efficiency isn’t an afterthought — it’s the core principle.
Responsibilities
We believe the future is adaptable, and not one-size-fits-all. We will lead in real-time efficient adaptation that combines algorithm with innovative interface design. Our global team—based in SF and beyond—brings together top talent in AI innovation. Backed by world-class investors, we're building Adaptable Intelligence.
Our Research Values
We are extremely driven and focused on one goal: building highly efficient, adaptable intelligence. We work as a single team, and place focus on a few key bets at a time. We are not driven by the goal of maximizing number of papers. We only publish when our work has a real world impact. If a simple method works well, we prioritize over a more complex and less performant method even if it is not as elegant. Our choices are always motivated by rigor and experimental success. We share back insights to the wider ecosystem to drive wider progress in the direction of continuous learning and highly efficient adaptable intelligence.
The Role
We are obsessed with efficiency— allowing for real-time evolution of AI depends on making adaptable intelligence extremely efficient. We co-design our algorithms with hardware requirements and serving in mind. We explore new research and algorithms within severe compute budgets. These budgets force us to innovate and collaborate across software, hardware, and algorithm.
This role is a part of the founding team, shaping both the research agenda and the product direction. You’ll collaborate with world-class peers and work at the cutting edge of AI efficiency research, where constraints drive creativity. You will contribute to building a company where efficiency isn’t an afterthought — it’s the core principle.
Responsibilities
- Innovation: lead our focused bets on real time adaptation, which include innovating on algorithmic recipes which result in large real time gains.
- Cross-Stack Optimization: collaborate across software, hardware, and algorithmic domains to achieve system-wide efficiency gains.
- Research & Development: explore new research directions in efficient machine learning, alignment, inference time scaling and adaptable systems. We will have a focus on gradient free techniques which produce large performance gains, as well as data efficient techniques which allow for rapid alignment and adaptation.
- Deep expertise in at least one area: model efficiency, distributed systems, hardware acceleration, or algorithmic optimization
- Systems thinking ability to understand and optimize across the full ML stack
- Strong programming skills in Python. Experience with deep learning frameworks (PyTorch, JAX, TensorFlow)
- Knowledge of model optimization techniques (RLHF, finetuning)
- A plus is experience in an industry lab with computing at scale
- Competitive salary + meaningful equity
- Learning and development budget to support your growth as you adapt
- Comprehensive medical benefits and generous PTO
- Annual travel stipend to explore somewhere new—because building global technology means staying adaptable to new places and perspectives
- Mission-driven team shaping the future of intelligence, where you'll enjoy high ownership and the opportunity to make a career-defining impact
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