Model Quantization

Model Quantization Developer Jobs

3 jobs found

Today

Software Engineer III, ML, TPU Efficiency, YouTube

YouTube Mountain View, CA

Mountain View, CA

Today

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

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Job Description

YouTube builds the machine learning systems that power the YouTube algorithm, and this role focuses on making those models more efficient across training and serving. You will help reduce training and serving costs while improving fleet utilization by working at the intersection of ML model optimization and TPU compiler co-design. The position is based in Mountain View, CA (onsite).

Compensation: USD 147,000 - 210,000 per year, plus 15% bonus target, equity, and benefits.

Responsibilities

Profile ML workloads to find compute and memory bandwidth bottlenecks, then optimize accelerator utilization to maximize compute efficiency.
Explore, implement, and productionize algorithmic efficiency techniques such as 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 such as accelerated linear algebra (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 the full ML software stack.
Experience with ML compilers and their internals, including writing compiler optimization passes.
Familiarity with accelerator hardware architectures (TPUs/GPUs).

Tech Stack

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

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

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2d ago

Lead Machine Learning Engineer, Human Sensing

Apple Seattle, WA

Seattle, WA

2d ago

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

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Job Description

Apple’s Human and Object Understanding (HOUr) team seeks a Lead Machine Learning Engineer (Technical Lead) to set technical direction for a multimodal Human Sensing group in Seattle.

Responsibilities

Serve as the primary technical lead with engineering management to define project scope, technical milestones, and roadmap execution
Set 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 reduce blind spots
Architect and lead the team’s evaluation framework and benchmarking pipelines, including custom metrics, evaluation scripts, and automated stress-testing tools
Lead failure mode analysis, root-cause investigation, and edge-case discovery to drive targeted model and data iterations
Coordinate day-to-day technical execution across multiple teams, including Evaluation, Integration, and Data Operations
Drive model optimization in partnership with integration and other partner teams
Train, fine-tune, and run experiments with state-of-the-art vision architectures when needed to unblock research or validate hypotheses
Maintain the team’s core codebase: author and review PRs, uphold engineering hygiene, and support rapid iteration velocity
Communicate technical strategy, performance trade-offs, and progress to stakeholders and senior leadership; mentor junior and mid-level engineers
Stay current with machine learning and multimodal foundation model trends, plus best practices in computer vision and natural language understanding

Requirements

Master’s or Ph.D. in Computer Science, Computer Engineering, or related field (or equivalent practical experience)
6+ years of industry experience in Computer Vision and Machine Learning
Proven Technical Lead or Staff-level experience: scoping projects, setting KPIs, and leading technical initiatives across cross-functional teams
Expertise in evaluating complex ML systems, defining benchmarking methodologies, and performing deep failure analysis
Experience coordinating engineering teams, mentoring peers, and partnering with management on roadmap execution
Strong attention to detail, ownership mindset, and agility in fast-evolving research environments
Deep proficiency in Python, PyTorch, and hands-on experience producing clean, maintainable code in 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), multimodal large language models (LLMs)
Large-scale vision-language models (VLMs)

Benefits

Comprehensive medical and dental coverage
Retirement benefits
Discounted products and free services
Reimbursement for certain educational expenses, including tuition
Discretionary bonuses or commission payments (may be eligible)
Relocation (may be eligible)
Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
Discretionary restricted stock unit awards (eligible)
Discounted Apple stock purchase if voluntarily participating in the Employee Stock Purchase Plan

Preferred Qualifications

Deep domain knowledge in face recognition, identity re-identification (ReID), biometrics, or visual human sensing (pose, expression, human-object interaction)
Hands-on collaboration with Data Collection & Annotation teams to design robust 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 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 & Location

Location: Seattle, WA (onsite)
Base pay range: USD 175,000 - 308,500 per year
Base pay depends on skills, qualifications, experience, and location
Apple benefit, compensation, and employee stock program eligibility and terms apply

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30d ago

Machine Learning Engineer - College Graduate

Qualcomm San Diego, CA

San Diego, CA

30d 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

This role supports Qualcomm AI Research by helping advance generative AI technology designed to run on the edge. You will contribute within a multi-disciplinary team, where the work spans architecture, development, testing, and deployment of on-device AI prototypes.

Role Overview

As a Machine Learning Engineer, you will focus on creating and validating prototype software for cutting-edge AI use cases on-device. The work is conducted in a dynamic research environment alongside researchers and software engineers using modern AI frameworks and tools.

Responsibilities

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

Required Qualifications

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

Technology Focus

Python and object-oriented software design
PyTorch and Generative AI (GenAI)
Neural network model optimization and model quantization
On-target deployment and edge inference
NPUs / ML accelerators and hardware acceleration
Android programming
C/C++ and embedded software
Algebraic operations optimization for hardware cores

Preferred Qualifications

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 hardware cores (plus).
Knowledge of C/C++ and embedded software.

Compensation and Location

Location: San Diego, CA (onsite)
Salary: USD 122,800 - 184,200 per year

Benefits

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

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Model Quantization Developer Jobs

Software Engineer III, ML, TPU Efficiency, YouTube

Lead Machine Learning Engineer, Human Sensing

Machine Learning Engineer - College Graduate

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