| Microsoft Careers

Microsoft

Hybrid

Quick summary

Work type: Hybrid
Location: —
Salary: $119,800–$234,700 / yr
Posted: 67 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $180k

This role $177k

$106k most similar roles pay here $248k

This role pays more than 64% of similar roles. Most pay $152,150–$207,350 — the shaded band above. At the midpoint, this role pays about $177k versus about $180k for comparable roles.

Based on 239 similar postings.

Employer

About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 1580 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 1408 roles with salary data.

Most-posted roles

View all roles at Microsoft

At a glance

TL;DR · | Microsoft Careers

Apply Now Log in to save

As a Senior Applied Scientist on the Core Recommendation Ranking team at Microsoft's AI Content Org, you will design and implement advanced ranking and recommendation models using deep learning and LLMs to enhance user engagement across various content experiences. Your day-to-day responsibilities include owning end-to-end ML pipelines from feature engineering to production inference optimization, collaborating with cross-functional teams to translate research into shipped features, and mentoring junior team members. You will work with cutting-edge technologies such as PyTorch or TensorFlow, Python, Spark, and Pandas, while tackling complex challenges in large-scale recommendation systems, generative AI, and agentic systems. This role requires a solid foundation in machine learning at scale, experience with LLM-based ranking, and a track record of delivering impactful ML models to production environments.

Skills

Python PyTorch TensorFlow Spark Pandas LLMs RAG CI/CD A/B Testing Docker Kubernetes AWS Azure Google Cloud Prometheus Grafana NeurIPS ICML KDD WWW RecSys SIGIR

What you'll do

Design and implement ranking models using deep learning and LLMs for Microsoft's content experiences.
Own end-to-end ML pipelines, including feature engineering, model training, and production inference optimization.
Apply state-of-the-art methods like contextual bandits and reinforcement learning to enhance recommendation systems.
Collaborate with cross-functional teams to translate research insights into shipped features impacting user engagement.
Mentor less experienced scientists and engineers while fostering a culture of technical excellence and knowledge sharing.

What we're looking for

4+ years of industry experience in applied science, machine learning, or deep learning at scale.
Solid foundation in recommendation systems, ranking models, and search relevance.
Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and cloud-scale ML infrastructure.
Track record of shipping ML models to production with measurable user impact.
Experience with LLM-based ranking, retrieval-augmented generation, or generative recommendation systems.

Save