Ai Accelerators

Ai Accelerators Engineer Jobs

4 jobs found

5d ago

Senior Staff Machine Learning Engineer

ValueBase Consulting San Jose, CA

San Jose, CA

5d ago

$70 - $80/hr Contract Senior Ai Accelerators Ai Ml

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Job Description

ValueBase Consulting is seeking a Senior Staff Machine Learning Engineer to support an AI-enhanced security processor effort. This contract role spans the full lifecycle, from model development and MLOps to silicon/NPU enablement, inference runtime optimization, and embedded integration with end-to-end deployment and monitoring.

Key Responsibilities

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

Required Qualifications

8-10+ years of hands-on AI/ML experience; Master’s degree required, PhD preferred
Hands-on experience with AI/ML infrastructure and performance, including GPU clusters, distributed training, inference-serving optimization, and MLOps pipelines
Experience in model and algorithm development, including designing, training, and evaluating ML models
Experience taking models into production, including feature engineering, data pipelines, and deployment
AI chip and hardware-aware ML experience, such as optimizing inference engines for a specific chip or adapting model architecture and quantization to chip constraints
Deep, hands-on expertise in at least 2 of the following specialty areas:
- NPU / AI-ACCELERATOR: hardening or extending an NPU core into production silicon, mapping models onto MAC or tensor-engine constraints, or NPU-aware RTL/DV work
- SYSTEMS / SYS-LEVEL SOFTWARE: BMC firmware, embedded Linux, RTOS (for example, 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, such as an agent-driven RTL/DV test runner or a hardware bring-up or manufacturing test harness
- CYBER SECURITY: AI-driven log or intrusion analysis, AI-assisted penetration testing, or firmware or hardware security

Relevant Technologies

GPU, AI-accelerator, MLOps pipelines, NPU
open RVV/tensor core, CoralNPU
BMC firmware, embedded Linux, RTOS, Zephyr
AI-assisted RTL/DV, RTL/DV
LLM, CV

Location and Hiring Constraints

San Jose, CA, USA (onsite)
Candidates should be located in California; W2 candidates are encouraged to apply
Any visa is fine

Compensation and Contract Details

Contract duration: 12 Months
Pay rate: USD 70 per hour on W2 or USD 80 per hour on C2C

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9d ago

Software Engineer, ML Accelerators

DeepMind San Francisco, CA

San Francisco, CA

9d ago

$174k - $252k/yr Full time Ai Accelerators Engineering Hardware Acceleration

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Job Description

Build the software foundation for next-generation AI inference at DeepMind. This onsite Software Engineer role in San Francisco focuses on the ML compiler stack and inference infrastructure that powers a next-generation compute platform, with an emphasis on HW acceleration and SW/HW codesign. You will join a team of scientists and engineers working on technology that helps shape the future of machine learning for Google and the broader industry.

As part of a highly collaborative environment, you will contribute to performance-critical systems that bridge AI workloads with low-level hardware operators. If you enjoy taking initiative and shipping end-to-end improvements across the stack, this coding role supports that drive.

Responsibilities

Own a direct full-stack software role focused on the ML compiler and inference infrastructure.
Design and develop an ML compiler stack that connects AI workloads to low-level hardware operators.
Design and build software infrastructure to enable high-performance inference.
Lead SW/HW codesign, including kernel optimization, performance tuning, and debugging.

Requirements

Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
Experience developing software with Python and C++.
Experience with ML hardware accelerators, ML compiler stacks (examples include JAX, PyTorch, XLA), and kernel development.

Preferred Qualifications

PhD degree in Computer Engineering, Computer Science, or a related field.
2 years of experience in full-stack system development for hardware accelerators.
2 years of experience with collaborative, hyper-scalar software development and engineering best practices.
Experience scoping, planning, and executing projects toward team goals in ambiguous environments.

Key Technologies

Python, C++, JAX, PyTorch, XLA

Compensation and Benefits

US compensation range: $174,000 - $252,000 USD per year, plus a 15% bonus target, equity, and benefits.

DeepMind is an AI lab with exceptional interdisciplinary teams focused on advancing AI development, supporting safety and ethics as top priorities. The organization emphasizes learning opportunities and varied career pathways, with global teams working to deliver high-quality impact and innovation for billions of users.

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9d ago

Software Engineer, ML Accelerators

DeepMind Mountain View, CA

Mountain View, CA

9d ago

$174k - $252k/yr Full time Ai Accelerators Hardware Acceleration Hardware Software Co Design

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Job Description

DeepMind is building a next-generation compute platform that pairs ML hardware acceleration with software and hardware co-design. In this onsite role in Mountain View, you will work on the ML compiler stack and inference infrastructure that translates AI workloads into high-performance execution across low-level hardware operators.

This Software Engineer position is centered on designing and developing the software components needed for fast, reliable inference, while collaborating closely on performance tuning and debugging that spans both software and hardware.

Key Responsibilities

Own a full-stack software role focused on the ML compiler and inference infrastructure.
Design and develop an ML compiler stack that bridges AI workloads with low-level hardware operators.
Design and develop software infrastructure aimed at enabling high performance inference.
Contribute to software and hardware co-design, including kernel optimization, performance tuning, and debugging.

Required Qualifications

Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
Experience in software development using Python and C++.
Experience with machine learning hardware accelerators, ML compiler stacks (for example, JAX, PyTorch, XLA), and kernel development.

Preferred Qualifications

PhD degree in Computer Engineering, Computer Science, or a related field.
2 years of experience in full-stack system development for hardware accelerators.
2 years of experience building collaborative, hyper-scalar software and applying engineering best practices.
Experience scoping, planning, and executing projects toward team goals in ambiguous environments.

Technology Focus

Python
C++
JAX
PyTorch
XLA

Location: Mountain View, CA (onsite)
Compensation: USD 174,000 - 252,000 per year

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1mo ago

Software Engineer III, ML, TPU Efficiency, YouTube

YouTube Mountain View, CA

Mountain View, CA

1mo ago Closed

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

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

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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Ai Accelerators Engineer Jobs

Senior Staff Machine Learning Engineer

Software Engineer, ML Accelerators

Software Engineer, ML Accelerators

Software Engineer III, ML, TPU Efficiency, YouTube

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