Microsoft Shopping aims to reinvent online shopping experiences for hundreds of millions of users worldwide by surfacing the most relevant products at the best prices from across the web, using cutting-edge information retrieval, recommendation systems, and generative AI.
Requirements
- 6+ years of experience utilizing Python
- 2+ years of experience with machine learning algorithms and statistical methods.
- 2+ years of experience with information retrieval / recommendation systems / NLP,(Natural Language Processing) or A/B testing.
- Experience with information retrieval, recommendation systems, NLP, and A/B testing.
- Deep understanding of machine learning algorithms and statistical methods.
- Scalability: Experience building large-scale data pipelines, distributed ML systems, or real-time inference services on cloud infrastructure.
- Modern ML Techniques: Familiarity with current AI advances, such as transformer models and LLM fine-tuning (e.g., PEFT/LoRA, reinforcement learning), as well as model compression/optimization methods for deployment.
Responsibilities
- Lead cutting-edge ML development: Design and refine advanced ranking algorithms using transformer-based architectures, semantic embeddings, and LLM fine-tuning techniques (e.g., knowledge distillation, LoRA, quantization) to deliver world-class relevance under strict latency constraints.
- Set the standard for evaluation: Define and evolve methodologies for both automated and human evaluations, ensuring comprehensive coverage and actionable insights.
- Architect scalable data systems: Build and optimize pipelines that transform massive product and interaction logs into structured datasets for model training and evaluation.
- Drive production excellence: Partner with engineering teams to deploy models at scale, optimize inference for p95 latency targets, and implement robust monitoring for reliability and performance.
- Shape AI strategy: Stay ahead of the curve on LLM research, prompting techniques, and evaluation frameworks and translate these advancements into real-world impact.
- Deliver business-critical insights: Lead deep-dive analyses on large-scale telemetry to uncover opportunities, guide product direction, and influence key metrics.
- Mentor and inspire: Provide technical leadership, coach top talent, and raise the bar for the team’s research and engineering practices.
Other
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
- Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
- Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
- Equivalent experience.
- Leadership: Keen interest for continuous learning and innovation in AI. Demonstrated technical leadership or mentorship experience is a plus (influencing technical direction, guiding team members)
