Model Quantization

Model Quantization Engineer Jobs

3 jobs found

29d ago

Software Engineer III, ML, TPU Efficiency, YouTube

YouTube Mountain View, CA

Mountain View, CA

29d ago

$147k - $210k/yr Full time Ai Accelerators Data Pipeline Data Processing

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Job Description

YouTube is hiring a Software Engineer III to improve the efficiency of the models that power the YouTube algorithm. This role focuses on reducing training and serving costs while increasing fleet utilization through work that spans ML workload profiling, algorithmic efficiency, and co-design between model implementation and TPU compiler aspects.

Work location: Mountain View, CA (onsite)

Compensation: $147,000 - $210,000 USD per year + 15% bonus target + equity + benefits

Responsibilities

Profile ML workloads to pinpoint compute and memory bandwidth bottlenecks, then optimize accelerator utilization to improve compute efficiency.
Explore, implement, and productionize algorithmic efficiency techniques, including low-precision quantization, knowledge distillation, parameter sharing, and attention optimizations.
Optimize auxiliary serving and distributed data pipelines, including data ingestion, feature transformation, embedding lookups, and memory caching to support real-time training and inference.
Collaborate with ML model developers and researchers to co-design hardware-friendly model architectures and deploy universal efficiency libraries.

Requirements

Bachelor's degree or equivalent practical experience.
2 years of experience programming in C++ or Python.
2 years of experience with software design and architecture.
2 years of experience testing and launching software products.
Experience with ML model optimization.
Experience with ML frameworks such as TensorFlow, JAX, and PyTorch, or ML compilers (e.g., XLA).

Preferred Qualifications

Master's degree or PhD in Computer Science or related technical fields.
Experience developing accessible technologies.
Experience debugging correctness and performance issues across all levels of the ML software stack.
Experience with ML compilers and internals, including writing compiler optimization passes.
Familiarity with accelerator hardware architectures (TPUs/GPUs).

Technology Stack

C++, Python, TensorFlow, JAX, PyTorch, XLA, TPUs, GPUs

Interview process: In most instances, this position requires in-person interviews as part of the hiring process.

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1mo ago

Lead Machine Learning Engineer, Human Sensing

Apple Seattle, WA

Seattle, WA

1mo ago Closed

$175k - $309k/yr Full time Manager Ai Ml Artificial Intelligence

This position is no longer accepting applications (closed Oct 22, 2026).

Job Description

Apple’s Human and Object Understanding (HOUr) team is seeking a Lead Machine Learning Engineer (Technical Lead) to shape the technical direction of a multimodal Human Sensing team. In this role, you will guide ML program scope, evaluation standards, dataset strategy, and hands-on on-device optimization while maintaining codebase quality.

Key Responsibilities

Serve as the primary technical lead in partnership with engineering management to define project scope, technical milestones, and roadmap execution, including rigorous KPI targets and quality benchmarks across demographics, environmental conditions, and device use cases.
Define dataset collection, annotation, and curation strategy in collaboration with the Data team to systematically address model blind spots.
Architect and lead the team’s core evaluation framework and benchmarking pipelines, including custom metrics, evaluation scripts, and automated tooling to stress-test models against production scenarios.
Lead failure mode analysis, root-cause investigation, and edge-case discovery to drive focused iterations on models and data.
Drive multi-team alignment across Evaluation, Integration, and Data Operations, coordinating day-to-day technical execution.
Partner with integration and other teams to drive model optimization.
Train, fine-tune, and run experiments with state-of-the-art vision architectures as needed to unblock research or validate hypotheses.
Act as the primary maintainer of the team’s core codebase, authoring and reviewing PRs, maintaining engineering hygiene, and supporting rapid iteration velocity.
Communicate technical strategy, performance trade-offs, and progress to stakeholders and senior leadership, and guide and mentor junior and mid-level engineers.
Stay current with advances in machine learning, multimodal foundation models, computer vision, and natural language understanding.

Required Qualifications

Master’s or Ph.D. in Computer Science, Computer Engineering, or a related field (or equivalent practical experience) with 6+ years of industry experience in Computer Vision and Machine Learning.
Proven experience in a Technical Lead or Staff-level capacity, including project scoping, KPI definition, and leading technical initiatives across cross-functional teams.
Strong expertise in evaluating complex ML systems, defining benchmarking methodologies, and performing deep-dive failure analysis.
Ability to coordinate engineering teams, mentor peers, and work closely with management on roadmap execution.
Strong attention to detail, ownership mindset, and agility in fast-evolving research environments.
Deep proficiency in Python and PyTorch, including hands-on experience writing clean, maintainable code and managing shared repositories.

Technologies

Python, PyTorch
Core ML
Quantization-aware training, knowledge distillation
Latency profiling, quantization, pruning
Multimodal foundation models
Computer vision, natural language understanding
Face recognition
Identity re-identification (ReID)
Foundation vision models
Large-scale Vision-Language Models (VLMs)
Large language models (LLMs) and multimodal large language models (LLMs)
Large-scale vision-language models (VLMs)

Preferred Qualifications

Deep domain knowledge in face recognition, identity re-identification (ReID), biometrics, or visual human sensing (pose, expression, human-object interaction).
Hands-on experience collaborating with Data Collection and Annotation teams to design collection protocols and active learning datasets.
Experience with on-device model optimization (quantization-aware training, knowledge distillation, Core ML conversion, latency profiling).
Experience with foundation vision models or large-scale Vision-Language Models (VLMs).
Hands-on experience training and scaling multi-modal LLMs or large-scale vision-language models (VLMs).
Experience with on-device ML, model optimization (knowledge distillation, quantization, pruning), or production-grade ML pipelines.
Research and innovation background demonstrated through publications in top-tier journals or conferences, patents, or impactful software developments.

Pay & Benefits

Base pay range: $175,000 to $308,500 per year (determined by skills, qualifications, experience, and location).
Comprehensive medical and dental coverage.
Retirement benefits.
Discounted products and free services.
Reimbursement for certain educational expenses, including tuition, for eligible formal education.
Discretionary bonuses or commission payments (may be eligible).
Relocation (may be eligible).
Opportunity to become an Apple shareholder via participation in Apple’s discretionary employee stock programs.
Eligible for discretionary restricted stock unit awards.
Can purchase Apple stock at a discount if voluntarily participating in the Employee Stock Purchase Plan.
Note: Benefits, compensation, and employee stock programs are subject to eligibility requirements and terms of the applicable plan or program.

Role Location

Seattle, WA (onsite).

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1mo ago

Machine Learning Engineer - College Graduate

Qualcomm San Diego, CA

San Diego, CA

1mo ago Closed

$123k - $184k/yr Full time Android Artificial Intelligence Data & Ai

This position is no longer accepting applications (closed Sep 24, 2026).

Job Description

Qualcomm’s AI Research team is looking for a Machine Learning Engineer - College Graduate to help advance Generative AI technology for on-device use. This role centers on building prototype software that brings cutting-edge AI capabilities to the edge, working within a multidisciplinary group of researchers and software engineers.

The position is based in San Diego, CA with an onsite work arrangement, and the target annual compensation range is USD 122,800 - 184,200.

Role Summary

You will be responsible for the full lifecycle of on-device prototype development, including architecture, implementation, validation, and deployment. Your work will support AI use cases that require efficient inference on constrained hardware environments.

Responsibilities

Collaborate in a dynamic research environment as part of a multi-disciplinary team using cutting-edge AI frameworks and tools.
Architect, design, develop, test, and deploy on-device prototype software for advanced AI use cases.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
Strong Python skills and object-oriented software design and implementation experience.
Knowledge of deep learning and machine learning frameworks, such as PyTorch.
Strong software design skills with a focus on usability.
Strong analytical, debugging, and problem-solving abilities.

Technologies

Python
Object-oriented software design
PyTorch
Generative AI (GenAI)
Neural network model optimization
Model quantization
On-target deployment
NPUs / ML accelerators
Android programming
C/C++
Embedded software
Hardware acceleration
Edge inference
Algebraic operations optimization for HW cores

Preferred Extra Experience and Skills

Knowledge of Generative AI (GenAI) technologies.
Knowledge of neural network model optimization and on-target deployment (plus).
Knowledge of NPUs / ML accelerators.
Knowledge of Android programming (plus).
Optimization of algebraic operations in algorithms for HW cores (plus).
Knowledge of C/C++ and embedded software.

Benefits

Competitive annual discretionary bonus program
Opportunity for annual RSU grants
Highly competitive benefits package

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Model Quantization Engineer Jobs

Software Engineer III, ML, TPU Efficiency, YouTube

Lead Machine Learning Engineer, Human Sensing

Machine Learning Engineer - College Graduate

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