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Staff ML Engineer

The Hіrеxрrеѕѕ

Hybrid in San Jose, California • Today

Easy Apply

Contract, Third Party

Depends on Experience

Staff Machine Learning Engineer

ServiceNow, Inc.

Santa Clara, California • Today

Full-time

USD 176,100.00 - 308,200.00 per year

Staff Machine Learning Engineer

Adobe Systems

San Jose, California • Today

Full-time

USD 172,500.00 - 306,625.00 per year

Staff ML Engineer

Axiado

San Jose, California • Today

Full-time

Staff Machine Learning Engineer

XPENG

Santa Clara, California • Today

Full-time

USD 179,400.00 - 303,600.00 per year

Sr / Staff Machine Learning Engineer

Adobe Systems

San Jose, California • Today

Full-time

USD 172,500.00 - 306,625.00 per year

Senior Staff Machine Learning Engineer

ServiceNow, Inc.

Santa Clara, California • Today

Full-time

USD 201,300.00 - 352,300.00 per year

Staff Machine Learning Engineer - VoIP Infrastructure

ServiceNow, Inc.

Santa Clara, California • Today

Full-time

USD 176,100.00 - 308,200.00 per year

Staff Machine Learning Engineer, Ads Modeling

Unity Microelectronics Inc.

Mountain View, California • Today

Full-time

USD 172,200.00 - 283,900.00 per year

Staff Machine Learning Engineer

Pinterest, Inc.

Palo Alto, California • Today

Full-time

USD 301,600.00 - 389,753.00 per year

Senior Staff Machine Learning Engineer, ML Platform

Apple, Inc.

Cupertino, California • Today

Full-time

Staff Machine Learning Engineer - AI/ML Compiler

Qualcomm Technologies

Santa Clara, California • Today

Full-time

USD 174,000.00 - 261,000.00 per year

Staff Machine Learning Engineer, Recommendation & AI Platform

NewsBreak

Mountain View, California • Today

Full-time

USD 230,000.00 - 300,000.00 per year

Senior Staff Machine Learning Engineer - Agentic AI

ServiceNow, Inc.

Santa Clara, California • Today

Full-time

USD 201,300.00 - 352,300.00 per year

Senior/Staff Machine Learning Engineer, Motion Planning

PlusAI

Santa Clara, California • Today

Full-time

USD 130,000.00 - 220,000.00 per year

Staff Machine Learning Engineer - LLM Quantization & Deployment

XPENG

Santa Clara, California • Today

Full-time

USD 215,280.00 - 364,320.00 per year

Staff Machine Learning Engineer, Agent Eval Platform

ServiceNow, Inc.

Mountain View, California • Today

Full-time

Staff Machine Learning Engineer - Ads Bidding & Pacing

Apple, Inc.

Cupertino, California • Today

Full-time

Staff Machine Learning Engineer, TikTok BRIC Community Health

TikTok

San Jose, California • Today

Full-time

USD 254,400.00 - 480,000.00 per year

Staff Machine Learning Engineer, GAI Search Relevance - Moveworks

ServiceNow, Inc.

Mountain View, California • Today

Full-time

USD 176,100.00 - 308,200.00 per year

Senior/Staff Machine Learning Engineer (Reinforcement Learning), Motion Planning

PlusAI

Santa Clara, California • Today

Full-time

USD 130,000.00 - 220,000.00 per year

Senior Staff Machine Learning Engineer, Agentic Systems - Moveworks

ServiceNow, Inc.

Mountain View, California • Today

Full-time

Staff Machine Learning Engineer, Agentic AI Harness & Quality - Moveworks

ServiceNow, Inc.

Mountain View, California • Today

Full-time

Staff Machine Learning Engineer, AI Platform & Agentic Apps

Robinhood

Menlo Park, California • 11d ago

Full-time

USD 255,000.00 - 300,000.00 per year

Staff Machine Learning Engineer, AI Platform & Agentic Apps

Robinhood

Menlo Park, California • Today

Full-time

USD 255,000.00 - 300,000.00 per year

Senior/Staff ML Engineer, ML Acceleration and Performance

Rivian

Palo Alto, California • Today

Full-time

USD 228,000.00 - 285,000.00 per year

Senior/Staff Machine Learning Engineer, Search & Knowledge Platforms

Apple, Inc.

Santa Clara, California • Today

Full-time

Staff ML Engineer, Perception Scene Understanding

Rivian

Palo Alto, California • Today

Full-time

USD 228,000.00 - 285,000.00 per year

Staff Machine Learning Engineer

Unity Microelectronics Inc.

Mountain View, California • Today

Full-time

USD 218,400.00 - 283,900.00 per year

Staff Machine Learning Engineer, Agentic App Platform

ServiceNow, Inc.

Mountain View, California • Today

Full-time

USD 176,100.00 - 308,200.00 per year

Job Details

Skills

RTL
Artificial Intelligence
Automated Testing
BMC
Deep Learning
Machine Learning Operations (ML Ops)
Cyber Security
DV
Embedded Linux
GPU
Machine Learning (ML)
Optimization
NPU
Mapping
RTOS
Zephyr
Penetration Testing
Firmware

Summary

Role: Staff ML Engineer

Location: San Jose, CA, USA

Job Description

About the role

We're looking for an ML engineer who works across the full stack from model to silicon — comfortable optimizing training and inference performance on GPU/AI-accelerator infrastructure, building or tuning models, and adapting model and inference-engine design to the constraints of the underlying chip and its NPU. You'll move fluidly between algorithm work, systems-level software, and infrastructure work, closing the loop end-to-end rather than owning just one layer of the stack. This is a rare chance to work the full cycle of AI silicon, from model down to chip — something most ML engineers at large companies never get access to.

What you'll do

Optimize training and inference performance across GPU and AI-accelerator infrastructure, including MLOps pipelines
Design, train, and evaluate ML models (deep learning, LLM, CV, or recommendation systems) and take them into production
Harden and extend NPU cores (e.g. building on an open RVV/tensor core like CoralNPU) into production silicon
Build or optimize inference engines and serving runtimes against real hardware constraints — latency, memory, and power
Work below the application layer where needed — BMC firmware, embedded Linux, or RTOS (e.g. Zephyr) — so AI features run reliably on real systems
Build automated test/verification harnesses that close the loop for AI-assisted RTL/DV, hardware bring-up, or manufacturing test
Apply ML to security — AI-driven log/intrusion analysis, AI-assisted penetration testing, or firmware/hardware security work
Collaborate closely with RTL/hardware, firmware, and QA teams to ship AI features end-to-end, from training through deployment and monitoring

Qualifications

What we're looking for

7+ years of hands-on AI/ML experience; Master's required, PhD preferred
Hands-on experience with AI/ML infrastructure and performance — GPU clusters, distributed training, inference-serving optimization, MLOps pipelines
Model / algorithm development experience — designing, training, and evaluating ML models
Experience taking models into production — feature engineering, data pipelines, deployment
AI chip / hardware-aware ML experience — optimizing inference engines for a specific chip, or adapting model architecture/quantization to chip constraints
Deep, hands-on expertise in at least 2 of the following 5 specialty areas — we don't expect all five:

NPU / AI-accelerator — hardening or extending an NPU core into production silicon, mapping models onto MAC/tensor-engine constraints, or NPU-aware RTL/DV work
Systems / Sys-level software — BMC firmware, embedded Linux, RTOS (e.g. Zephyr), or other low-level system software
Inference engine / runtime — built or materially optimized an inference engine or serving runtime against real hardware constraints
Test / verification harness — built an automated harness that closes a loop, e.g. an agent-driven RTL/DV test runner or a hardware bring-up / MFG test harness
Cyber security — AI-driven log/intrusion analysis, AI-assisted penetration testing, or firmware/hardware security

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91133531
Position Id: 9109555
Posted 9 hours ago

Fitment

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Contact the job poster

Prince Kumar Ravi

Recruiter @ The Hіrеxрrеѕѕ

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On-device ML Performance Engineer, Graphics, Games and Machine Learning

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The On-Device Machine Learning team at Apple is responsible for enabling the Research to Production lifecycle of cutting edge machine learning models that power magical user experiences on Apple's hardware and software platforms. Apple is the best place to do on-device machine learning, and this team sits at the heart of that discipline, interfacing with research, SW engineering, HW engineering, and products. The On-device ML Performance team has the responsibility to analyze latency, memory, p

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ML Algorithm Mapping and Performance Engineer, Core ML

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Job Details

Skills

RTL
Artificial Intelligence
Automated Testing
BMC
Deep Learning
Machine Learning Operations (ML Ops)
Cyber Security
DV
Embedded Linux
GPU
Machine Learning (ML)
Optimization
NPU
Mapping
RTOS
Zephyr
Penetration Testing
Firmware

Summary

Role: Staff ML Engineer

Location: San Jose, CA, USA

Job Description

About the role

What you'll do

Optimize training and inference performance across GPU and AI-accelerator infrastructure, including MLOps pipelines
Design, train, and evaluate ML models (deep learning, LLM, CV, or recommendation systems) and take them into production
Harden and extend NPU cores (e.g. building on an open RVV/tensor core like CoralNPU) into production silicon
Build or optimize inference engines and serving runtimes against real hardware constraints — latency, memory, and power
Work below the application layer where needed — BMC firmware, embedded Linux, or RTOS (e.g. Zephyr) — so AI features run reliably on real systems
Build automated test/verification harnesses that close the loop for AI-assisted RTL/DV, hardware bring-up, or manufacturing test
Apply ML to security — AI-driven log/intrusion analysis, AI-assisted penetration testing, or firmware/hardware security work
Collaborate closely with RTL/hardware, firmware, and QA teams to ship AI features end-to-end, from training through deployment and monitoring

Qualifications

What we're looking for

7+ years of hands-on AI/ML experience; Master's required, PhD preferred
Hands-on experience with AI/ML infrastructure and performance — GPU clusters, distributed training, inference-serving optimization, MLOps pipelines
Model / algorithm development experience — designing, training, and evaluating ML models
Experience taking models into production — feature engineering, data pipelines, deployment
AI chip / hardware-aware ML experience — optimizing inference engines for a specific chip, or adapting model architecture/quantization to chip constraints
Deep, hands-on expertise in at least 2 of the following 5 specialty areas — we don't expect all five:

NPU / AI-accelerator — hardening or extending an NPU core into production silicon, mapping models onto MAC/tensor-engine constraints, or NPU-aware RTL/DV work
Systems / Sys-level software — BMC firmware, embedded Linux, RTOS (e.g. Zephyr), or other low-level system software
Inference engine / runtime — built or materially optimized an inference engine or serving runtime against real hardware constraints
Test / verification harness — built an automated harness that closes a loop, e.g. an agent-driven RTL/DV test runner or a hardware bring-up / MFG test harness
Cyber security — AI-driven log/intrusion analysis, AI-assisted penetration testing, or firmware/hardware security

Dice Id: 91133531
Position Id: 9109555
Posted 9 hours ago

Fitment

Dice Job Match Score™

To see how well you match this job, please log in or create an account.

Once logged in, be sure to complete your profile to get the most accurate match score.

Contact the job poster

Prince Kumar Ravi

Recruiter @ The Hіrеxрrеѕѕ

View Profile

Create job alert

Never miss an opportunity! Create an alert based on the job you applied for.

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