below marketmost similar roles pay hereabove market
This role pays less than
81%
of similar roles. Most pay
$192,050–$247,228
— the blue band above.
At the midpoint, this role pays about
$177k
versus about
$220k
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.
The Senior Machine Learning Engineer joins a multi-disciplinary team of researchers and engineers to design, train, and optimize generative models for multimodal scientific discovery. In this role, you will lead the training of large language and multimodal models by developing, managing, and debugging training workflows. You will scale and optimize training runs, identify efficiency gains, and provide technical leadership across the organization. Key responsibilities include refining data mixes, implementing data and model parallelism techniques, and performing model distillation. You must possess deep experience with PyTorch or Jax and the ability to profile training and inference code to mitigate performance bottlenecks. This work focuses on translating research into impactful solutions to accelerate the rate of discovery and further the frontier of human knowledge.
What does a Machine Learning Engineer earn?
Median $235750 from 323 postings across 48 companies.
Lead the training of large language and multimodal models.
Develop, manage, and debug complex training workflows.
Scale and optimize training runs to achieve efficiency gains.
Mentor team members and provide technical leadership in areas of expertise.
Advise on strategic directions and technical approaches for research projects.
Profile training and inference code to identify and mitigate performance bottlenecks.
Refine data mixes and implement data/model parallelism techniques.
What we're looking for
Bachelor's Degree in Computer Science or related technical field and 4+ years of technical engineering experience in ML-related work (or equivalent).
Doctorate in Computer Science or related technical field (preferred).
Hands-on technical experience in distributed training of large language/multimodal models, optimizing training workflows, or model distillation (preferred).
Deep experience with PyTorch or Jax (preferred).
Experience designing, optimizing, and monitoring generative modeling training workflows (preferred).
Familiarity with profiling training and/or inference code to identify and mitigate performance bottlenecks (preferred).
Comfort with refining data mixes, midtraining, post-training, data/model parallelism techniques, or model distillation (preferred).
Demonstrated communication skills with the ability to present complex technical concepts to a broad audience (preferred).
Machine Learning
C++
Python
PyTorch
TensorFlow
Computer Vision
Multi-sensor Fusion
Deep Learning
TensorRT
Transformers
Data Pipelines
Model Optimization
NVIDIA DRIVE AV
Object Detection
Semantic Segmentation