
Senior Applied Scientist - LLM
- Vancouver, BC
- $203,900 per year
- Permanent
- Full-time
- Drive data exploration and analysis by collecting initial datasets, selecting appropriate analytical techniques, and applying foundational statistical methods to extract insights.
- Leverage generative AI and agentic orchestration to build intelligent systems that powers multi modality media processing.
- Design and implement advanced LLM-based architectures and agentic systems for real-world product scenarios.
- Apply and adapt research ideas to solve practical challenges in reasoning, planning, memory, and alignment.
- Collaborate with cross-functional teams—including product, engineering, and research—to align efforts and deliver high-impact solutions.
- Champion customer-centric solutions by understanding business goals, identifying growth opportunities, and managing expectations throughout the project lifecycle.
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- 4+ years of experience in applied machine learning, with a focus on LLMs, agent systems, or reinforcement learning.
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
- Hands-on experience with model training pipelines using PyTorch, TensorFlow, JAX, or similar frameworks.
- Familiarity with distributed training, prompt engineering, evaluation strategies, and model deployment best practices.
- Coding and debugging skills, and comfort working in cross-functional, agile environments.