Senior Applied Scientist

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We are seeking a highly motivated Senior Applied Scientist to join our team in building cutting-edge visual models optimized for on-device inference. This role is ideal for candidates passionate about deep learning, model optimization, and deploying efficient AI solutions on constrained hardware platforms.

As a Senior Applied Scientist, you will work with a cross-functional team to bring vision and UI-centric models to life by training models, developing datasets for training/evaluation, and balancing requirements including inference time, power consumption, and model accuracy. This opportunity will allow you to grow your capabilities with deep learning, model optimization, and deploying efficient AI solutions on constrained hardware platforms.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Required Qualifications:

• 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.

• Solid experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and model compression techniques.
• Experience with model evaluation metrics and benchmarking across platforms.

Preferred Qualifications:

• Prior experience training models with custom architectures and tuning architectures to optimize for inference time.
• Proven track record in quantization, performance tuning, and deploying models on edge devices.
  
• Familiarity with silicon-specific optimization strategies.
  
• Hands-on experience with Qualcomm QNN, Intel OpenVINO, or similar toolchains.

Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications for the role until September 14, 2025.

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• Be part of a team contributing to pre- and post-training efforts for visual models pertaining to screen understanding.
• Explore and implement Transformer-based architectures and suggest architectural improvements for efficiency and scalability.
• Use techniques like distillation, adapters, and Low Rank Adapters (LoRAs) to build upon existing models.
• Optimize models for on-device inference using techniques such as quantization and debugging models.
• Conduct performance tuning and model evaluation across diverse silicon platforms (e.g., Neural Processing Units--NPUs, GPUs, custom accelerators).
• Collaborate with cross-functional teams to integrate models into production pipelines and validate performance in real-world scenarios.
• Contribute to internal model libraries and tooling for deployment across multiple hardware toolchains.
• Embody our Culture and Values.