Model Optimization

Model Optimization Engineer Jobs

4 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

Apply Now

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.

View full job page →

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).

View full job page →

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

View full job page →

2mo ago

Principal Machine Learning Engineer

On behalf of Next Deavor New York, NY

New York, NY

2mo ago Closed

$200k - $250k/yr Full time Ai Ml Artificial Intelligence Data Pipeline

This position is no longer accepting applications (closed Sep 13, 2026).

Job Description

The Principal Machine Learning Engineer will own the end-to-end machine learning infrastructure behind real-time compliance enforcement systems, including training, evaluation, and production serving. This is a hybrid role based in the New York City Metro area, with 3 days onsite.

Role Focus

Own ML infrastructure for real-time compliance enforcement systems, driving model training, evaluation, and production serving. The work includes building reliable pipelines and deployment mechanisms that support safe model updates and ongoing quality monitoring.

Responsibilities

Build and own training pipelines covering data preparation, reproducible fine-tuning runs, experiment tracking, and release automation
Build evaluation infrastructure with automated evaluation runs, regression gates, dashboards, and dataset versioning
Own production model serving including low-latency inference, batching, optimization, autoscaling, and cost management
Ship model updates safely using versioning, canarying, rollback, and drift monitoring
Create repeatable adaptation workflows to update models for new domains and customer needs
Turn expert labels and reviewer feedback into clean training and evaluation datasets
Set the engineering bar for ML infrastructure as the team grows

Requirements

8+ years of software engineering experience, including 4+ years building infrastructure for ML or LLM systems in production
Hands-on experience with the modern LLM stack: PyTorch, distributed training, fine-tuning at scale (for example LoRA, SFT), and inference engines such as vLLM or TensorRT-LLM
Experience building evaluation harnesses, regression gates, or dataset pipelines, with strong understanding of precision, recall, and calibration
Proven ownership of production model serving with real constraints for latency, reliability, and cost
Strong fundamentals in Python, containers, CI/CD, cloud infrastructure, and observability
Ability to scope work, ship frequently, and make pragmatic build-vs-buy decisions
Experience collaborating closely with research partners and defining clear interfaces

Technologies

PyTorch
LoRA
SFT
vLLM
TensorRT-LLM
Python
Containers
CI/CD
Cloud infrastructure
Observability

Additional Skills That May Help

Experience productionizing small or specialized language models
Experience with structured-output serving or constrained decoding in production
Prior work in regulated or high-stakes domains (fintech, healthcare, legal, trust and safety)
Experience deploying models into customer-controlled environments

Compensation and Location

Pay range: USD 200,000 - 250,000 per year
Location: New York, NY (hybrid, 3 days onsite)
Work location details: Hybrid remote in New York, NY 10001

How to Apply

This role may fill quickly. Submit your resume to be considered.

View full job page →

Model Optimization Engineer Jobs

Software Engineer III, ML, TPU Efficiency, YouTube

Lead Machine Learning Engineer, Human Sensing

Machine Learning Engineer - College Graduate

Principal Machine Learning Engineer

Get Model Optimization Engineer Jobs alerts