# Senior Applied Scientist

**Company**: Microsoft AI
**Location**: Vancouver
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: CAD $114,400 – CAD $203,900 per year
**Category**: Engineering
**Industry**: Technology

**Apply**: https://microsoft.ai/job/senior-applied-scientist-7/
**Canonical**: https://yubhub.co/jobs/job_9e63acec-fe1

## Description

## Summary

Microsoft AI are looking for a talented Senior Applied Scientist at their Vancouver office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

## About the Role

As a Senior Applied Scientist, you'll lead the science behind Discover's ranking and content-quality stack, combining LLMs, multimodal models, and large-scale recommender systems to drive measurable gains in engagement, satisfaction, and trust. You will set technical direction, mentor a high-caliber science cohort, and partner closely with engineering, PM, UXR, and policy to ship end-to-end outcomes.

## Accountabilities

- Lead content-quality understanding at scale.

- Advance the recommendation & ranking stack.

- Own evaluation and experimentation.

- Champion safety & trust.

- Scale E2E ML systems.

- Mentor & influence.

- Stay close to users.

## The Candidate we're looking for

**Experience:**

- 4+ years related experience (e.g., statistics predictive analytics, research).

**Technical skills:**

- Expertise with LLMs (prompting, RAG, Parameter-Efficient Fine-Tuning), multimodal modeling, and retrieval-augmented recommendation.

- Familiarity with counterfactual learning and multi-objective optimization.

**Personal attributes:**

- Strong communication and collaboration skills.

- Ability to work in a fast-paced environment.

## Benefits

- Competitive salary.

- Comprehensive benefits package.

- Opportunities for professional growth and development.

## Skills

### Required
- LLMs
- multimodal modeling
- retrieval-augmented recommendation
- counterfactual learning
- multi-objective optimization

### Nice to have
- Python
- PyTorch
- TensorFlow