Senior Applied Scientist

Microsoft

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: —
Salary: $119,800–$234,700 / yr
Posted: 5 days ago
Freshness: Confirmed live today
Closes: Apr 19, 2027

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $192k

This role $177k

$106k $248k

below market most similar roles pay here above market

This role pays less than 54% of similar roles. Most pay $162,000–$222,500 — the blue band above. At the midpoint, this role pays about $177k versus about $192k for comparable roles.

Based on 240 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 694 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 651 roles with salary data.

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At a glance

TL;DR · Senior Applied Scientist

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The Senior Applied Scientist joins the Frontier Tuning team to advance large-scale model post-training and adaptation for enterprise environments. This role involves designing and developing methods to adapt foundation models, including language, diffusion, and multimodal models, for specific tasks like document understanding and workflow automation. The scientist will build scalable infrastructure and tooling for training, steering, evaluating, and securely deploying AI systems. Key responsibilities include implementing reinforcement learning, supervised fine-tuning, and parameter-efficient adaptation techniques like LoRA-style methods. The position requires expertise in Transformer architectures, RLHF, RLAIF, and inference-time controllability. Candidates must utilize Python and machine learning frameworks like PyTorch to solve technical problems related to latency, safety, privacy, and compute efficiency while translating customer requirements into scalable model adaptation solutions.

What does a Applied Scientist earn?

Median $208800 from 61 postings across 10 companies.

See salary data

Skills

Reinforcement Learning supervised fine‑tuning RLHF RLAIF Transformer Architecture LoRA Multimodal Models Diffusion Models Python PyTorch Inference‑time steering Scalable ML Systems Foundation Models

What you'll do

Design and develop methods to adapt foundation models for enterprise-specific tasks like document understanding and workflow automation.
Develop post-training components including reinforcement learning, fine-tuning, and parameter-efficient adaptation techniques.
Implement and evaluate adaptation approaches under enterprise constraints such as latency, safety, privacy, and compute efficiency.
Build tooling for the evaluation, debugging, and development of foundation models.
Translate product and customer requirements into scalable model adaptation solutions.
Explore post-training techniques to improve domain specialization, tool use, and agentic behaviors.
Drive technical work from initial concept to prototype to deliver new methods and systems components.
Document technical approaches and share best practices to improve organizational capabilities in secure model deployment.

What we're looking for

Bachelor's degree with 4+ years experience, Master's with 3+ years, or Doctorate with 1+ year in a related field.
Equivalent experience to the degree and years of experience requirements.
Ability to pass the Microsoft Cloud background check.
Master's degree with 6+ years experience or Doctorate with 3+ years experience in a related field (preferred).
3+ years experience creating publications, patents, or libraries (preferred).
3+ years experience conducting research as part of a research program (preferred).
2+ years experience with Python and machine learning frameworks like PyTorch (preferred).
2+ years experience building scalable ML systems or pipelines for training, adapting, or deploying AI models (preferred).

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