Applied Research Scientist (AI)

TL;DR

Applied Research Scientist (AI): Leading the design, development, and deployment of scalable GenAI applications for professional services with an accent on LLM workflows, agent-driven solutions, and cloud-native architecture. Focus on implementing high-stakes AI solutions into real-world enterprise environments, optimizing model performance, and driving innovation through research and collaboration.

Location: Must be based in or able to work from Toronto, Ontario or Palo Alto, California (Hybrid model).

Company

An innovative AI startup transforming professional services through agent-driven solutions and deep domain expertise.

What you will do

• Design and implement robust, cloud-native GenAI solutions, primarily on Azure.
• Fine-tune LLMs, enhance data retrieval systems, and optimize prompt engineering and agent plans.
• Lead the end-to-end delivery of high-stakes AI projects for enterprise clients.
• Stay at the forefront of AI trends and contribute to open-access research and academic collaborations.
• Mentor junior researchers and engineers to foster technical growth.
• Collaborate with cross-functional teams to align AI strategy with business needs.

Requirements

• Ph.D. in Computer Science, Engineering, Neuroscience, Robotics, or a related field.
• 5+ years of professional experience in Python development and deploying ML/GenAI applications.
• 5+ years of research experience in next-generation technologies like multi-modal systems, agents, or reinforcement learning.
• 2+ years of hands-on experience building and deploying AI/ML solutions in Azure.
• Proven track record of significant results in top-tier AI conferences or publications.
• Advanced proficiency in Python and frameworks such as PyTorch, Tensorflow, or JAX.

Nice to have

• Experience with GenAI frameworks like LangChain or DSPy.
• Experience with LLMs from OpenAI, Anthropic, Google, or Meta.
• Strong background in RAG systems and chatbot development.

Culture & Benefits

• Competitive compensation tailored to experience.
• Hybrid working model for improved work-life balance.
• Opportunities for professional development and leadership roles.
• Exposure to transformative technologies in a fast-paced startup environment.