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Machine Learning Hardware Jobs (NOW HIRING)

Avride

Machine Learning Engineer

Austin, TX

Optimize inference performance, model compression, and deployment across various hardware platforms ... Strong understanding of fundamental machine learning algorithms and neural network techniques.

Spear AI

Machine Learning Engineer

They are seeking a skilled Machine Learning Engineer to build and deploy production ML systems for ... Spear AI develops AI-powered software and hardware for maritime operations. Founded in 2021, the ...

New

1872 Consulting

Machine Learning Engineer

Chicago, IL

Strong software, hardware, and systems development understanding * Programming fluency in C/C++ and ... Hands-on experience applying machine learning and deep learning to vision data, preferably direct ...

Apple

Machine Learning Compiler Engineer

Sunnyvale, CA · On-site

If you're passionate about pushing the boundaries of AI and hardware optimization, we want you to join our team! As a Machine Learning Compiler Engineer on the Apple Neural Engine (ANE) team, you'll ...

Apple

Machine Learning Compiler Engineer

Sunnyvale, CA · On-site

If you're passionate about pushing the boundaries of AI and hardware optimization, we want you to join our team! As a Machine Learning Compiler Engineer on the Apple Neural Engine (ANE) team, you'll ...

Apple

Camera Machine Learning Engineer

Bodega Bay, CA

$147.40K - $272.10K/yr

Join Apple's Camera Hardware Engineering team and help us redefine the camera experience for ... Description As a Machine Learning Engineer in the Camera Hardware Engineering group you will be ...

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

Machine Learning Engineer We're seeking a skilled Machine Learning Engineer to build and deploy ... Whether you're joining our Hardware, Software, or Services division, you'll work alongside talented ...

Root Access Inc

Machine Learning Engineer

New York, NY · On-site

We help mission-critical hardware teams leverage purpose-built AI to program and certify their systems faster. Role Description: The Machine Learning Engineer will be responsible for designing and ...

Apple

Camera Machine Learning Engineer

San Francisco, CA · On-site

$147.40K - $272.10K/yr

Camera Machine Learning Engineer - Camera Hardware Are you a passionate Machine Learning Engineer with a deep love for photography? Join Apple's Camera Hardware Engineering team and help us redefine ...

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How much do machine learning hardware jobs pay per hour?

As of Jun 3, 2026, the average hourly pay for machine learning hardware in the United States is $24.59, according to ZipRecruiter salary data. Most workers in this role earn between $17.55 and $27.88 per hour, depending on experience, location, and employer.

What is a Machine Learning Hardware job?

A Machine Learning Hardware job involves designing, optimizing, and developing specialized hardware to accelerate machine learning workloads. Professionals in this field work on hardware architectures like GPUs, TPUs, FPGAs, and custom accelerators to improve efficiency, performance, and power consumption. They collaborate with software engineers and data scientists to optimize hardware-software co-design. This role requires expertise in computer architecture, parallel computing, and low-level programming.

What are the key skills and qualifications needed to thrive in the Machine Learning Hardware position, and why are they important?

To thrive in Machine Learning Hardware, you need a solid background in computer engineering, digital design, and machine learning principles, often supported by a degree in electrical engineering, computer engineering, or a related field. Familiarity with hardware description languages (such as VHDL or Verilog), simulation tools, FPGA/ASIC development platforms, and possibly certifications in hardware design or ML accelerators is valuable. Collaboration, problem-solving, and the ability to communicate complex technical ideas effectively are essential soft skills. These skills enable you to design and optimize specialized hardware solutions that accelerate machine learning workloads and foster interdepartmental innovation.

What are the typical day-to-day responsibilities for a Machine Learning Hardware engineer?

As a Machine Learning Hardware engineer, your daily tasks often include collaborating with data scientists and software engineers to understand computational requirements, designing and prototyping hardware accelerators, and optimizing existing architectures for improved performance and efficiency. You might work with simulation tools to model new designs, validate hardware functionality, and troubleshoot issues during integration. The role typically involves both independent technical work and teamwork across hardware and AI/ML departments. This position requires keeping up to date with emerging technologies to ensure your solutions remain cutting-edge and competitive in the fast-evolving landscape of artificial intelligence.
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What cities are hiring for Machine Learning Hardware jobs? Cities with the most Machine Learning Hardware job openings:
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Machine Learning Hardware jobs near you
Infographic showing various Machine Learning Hardware job openings in the United States as of May 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $51,154 per year, or $24.6 per hour.

Machine Learning Engineer

Avride

Austin, TX

Other

Posted 10 days ago

Job description

About the Team

Avride develops autonomous vehicle and delivery robot technology, leveraging deep expertise in autonomous systems. With the recent launch of our robotaxi service in Dallas, we are accelerating innovation and redefining the future of mobility.

Our team builds self-driving solutions from the ground up, with machine learning at the core of our development pipeline to enable safe and intelligent navigation. We design and deploy state-of-the-art models to address key challenges in autonomous systems, utilizing advanced deep learning architectures such as Convolutional Neural Networks (CNNs), Transformers, and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard applications, ensuring robust and efficient operation. Your work will directly contribute to enhancing the performance, safety, and reliability of Avride's autonomous vehicles and delivery robots.

About the Role

We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In this role, you will conduct experiments, manage large-scale datasets, and implement deep learning models tailored for autonomous systems.
You will utilize cloud platforms, orchestration tools, and machine learning frameworks to develop scalable and efficient solutions. Additionally, you will analyze the latest research, assess the applicability of emerging deep learning techniques, and drive innovation in autonomous vehicle technology.

What You'll Do
  • Develop and Optimize Machine Learning Models: Design, implement, and refine deep learning models to ensure efficiency, scalability, and robustness. This may include developing models for understanding a self-driving vehicle's surroundings or predicting the intentions of other road users.
  • Curate and Manage Large-Scale Datasets: Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for training and evaluation.
  • Enhance and Maintain Training Pipelines: Develop efficient workflows for training, validation, and testing, incorporating distributed training, hyperparameter tuning, and automated monitoring.
  • Improve Model Deployment and Efficiency: Optimize inference performance, model compression, and deployment across various hardware platforms.
  • Explore and Apply Cutting-Edge ML Techniques: Stay up to date with advancements in deep learning and experiment with novel approaches to improve model performance.
  • Collaborate with Cross-Functional Teams: Work closely with researchers, software engineers, and robotics experts to integrate machine learning solutions into real-world autonomous systems.
What You'll Need
  • Strong understanding of fundamental machine learning algorithms and neural network techniques.
  • Expertise in at least one modern machine learning domain, such as computer vision, large language models, or generative AI.
  • At least three years of experience developing neural network-based algorithms, including data collection, training, and deployment.
  • Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, along with PySpark, NumPy, and SciPy.
  • Working knowledge of C++ and SQL.
  • Ability to quickly absorb new concepts by reviewing research papers, technical reports, and documentation.
  • Strong collaboration and communication skills, with the ability to align technical work with business objectives and drive results.
Nice to Have
  • Advanced degree in Computer Science, Machine Learning, Robotics, or a related field.
  • Experience developing ML algorithms for autonomous vehicles or robotics applications.
  • Familiarity with neural network deployment and optimization tools such as triton, TensorRT, or similar frameworks.
  • Proven ability to set and achieve mid- and long-term goals, prioritize tasks, and meet deadlines independently.
  • Experience working in cross-functional teams within a multidisciplinary environment.
  • Publications in top-tier ML conferences or contributions to patent applications or ML-related open-source projects.

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