Artificial Intelligence Researcher
- Vancouver, BC, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Experience
- 5+ years of applied research experience in industry labs or startups.
- Posting language
- English
- Posted
Original job description
We’re looking for a Senior AI Researcher to bridge frontier research with product innovation. You’ll focus on advancing breakthroughs in AI and machine reasoning and translating them into applied systems that people use every day. You’ll help invent, prototype, and scale the core technologies that power Aloe. You will work in a close-knit team that spans philosophy, engineering, cognitive science, UX, and operations, in our shared mission to invent, implement, and deliver the most significant step change to AI since the introduction of ChatGPT.
Come close the imagination gap on how we build human-level AI and what it should be used for. Our team has unmatched clarity of purpose, and unmatched ambition. We seek to be the best in the world: on trust, capability, and ensuring the benefits of AI accrue to everyone.Culture
We welcome teammates who want to do their life’s best work over the next 5 years. We are exceptional at what we do, and see ourselves as scientists, philosophers, and builders who enjoy working in the fellowship of other intrinsically motivated people. We strive to be Level 5 humans, co-creating a deliberately developmental atmosphere.
What you can expect working here to be like:- Speed: Our ambition will only be reached if we are laser focused on the essential and move with purpose. You will consistently find yourself not knowing how to proceed and needing to figure out how to take next steps despite that.
- Opportunity: We are at an inflection point for our species and are bending the world toward one we want to live in – where everyone is safe and has access to the opportunities to express their innate creativity and pursue their deepest meaning.
- Optimism: We are high fun, ultimately high agency.
- Comfort with being uncomfortable: You should expect to always be in your “developmental zone,” which necessitates feeling inadequate and uncomfortable. Personal development is a core practice for continually leveling-up as technologist and as a human. Everyone is a senior person.
- Support: We are all in this together, and here to help each other succeed. We’ve got empathy for each other because we’re all experiencing the discomfort of growth together. We’ll only win as a team, so the only valid use of ego here is to fuel our creativity with it.
- Collaboration: We are building the rocketship as we’re flying it. We’re all responsible for finding ways to make ourselves and our team more effective. We’re run by ideas, not hierarchy.
- The opportunity to see your work directly impact people’s lives at scale.
- The chance to do the best work of your life surrounded by some of the most capable humans on the planet.
- Compensation at the high end of the market for the role and company stage, including benefits.
- Unceasing opportunities for career growth.
- Lead research projects that directly inform and improve product capabilities.
- Develop and test novel approaches in areas like epistemic reasoning, risk, and abductive inference using both new and existing language models and various training methodologies.
- Rapidly prototype and iterate on research ideas, with an eye toward production readiness.
- Collaborate with engineering teams to integrate new models into live systems.
- Mentor researchers and engineers, raising the bar for scientific and technical rigor throughout the org.
- Track and adapt cutting-edge work from the research community into practical solutions.
- Advanced degree in computer science, machine learning, or related field; requirement may also be met with equivalent research experience.
- 5+ years of applied research experience in industry labs or startups.
- Proven ability to take ideas from concept to prototype to production.
- Strong expertise in one or more areas: large language models, reasoning, reinforcement learning, self-supervised learning, or knowledge representation.
- Skilled in Python and modern ML frameworks (PyTorch, JAX, TensorFlow).
- Excellent communication and collaboration skills; comfortable working across disciplines.
- Track record of impactful applied work (product launches, open-source contributions, patents, or widely used systems).
- Experience with evaluation and benchmarking of applied ML systems.
- Background in building human-in-the-loop, verification, or auto-escalation systems in AI.
- Familiarity with safety, interpretability, or robustness in production models.
- Experience mentoring applied research teams.
Send us a note at join@aloe.inc.
More about this job
Responsibilities
Lead applied research projects that improve product capabilities, developing and testing novel reasoning approaches and rapidly prototyping ideas for production. Collaborate with engineering to integrate models into live systems, mentor colleagues, and translate cutting-edge research into practical solutions.
Requirements
Requires an advanced degree in computer science, machine learning, or a related field, or equivalent research experience, plus at least five years of applied research experience. Candidates should have expertise in one or more relevant AI areas, proficiency in Python and modern ML frameworks, a record of taking research into production, and strong communication and collaboration skills.
Skills
- Applied AI Research
- Large Language Models
- Machine Reasoning
- Epistemic Reasoning
- Abductive Inference
- Reinforcement Learning
- Self-Supervised Learning
- Knowledge Representation
- Python
- PyTorch
- JAX
- TensorFlow
- Model Evaluation
- AI Safety
- Interpretability
- Mentoring
Benefits
- Benefits
- Career Growth Opportunities
Visa sponsorship
Not detected in the job text
Categories
- Science & Research
- Technology
- Software
- Engineering
- Data & Analytics
Keywords
- Artificial Intelligence
- Applied Research
- Machine Learning
- Large Language Models
- Machine Reasoning
- Epistemic Reasoning
- Risk Modeling
- Abductive Inference
- Reinforcement Learning
- Self-Supervised Learning
- Knowledge Representation
- Python
- PyTorch
- JAX
- TensorFlow
- Model Evaluation
- Benchmarking
- Human-in-the-Loop Systems
- Verification Systems
- Auto-Escalation Systems
- AI Safety
- Interpretability
- Robustness
- Production ML Systems
- Prototyping
- Mentoring