Edge AI Engineer
$134K - $177K/yr
... TinyML technologies. Qualifications : Required : • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Electronics, Embedded Systems, Electrical Engineering, Robotics, or a ...
New
Edge AI Engineer
$134K - $177K/yr
... TinyML technologies. Qualifications : Required : • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Electronics, Embedded Systems, Electrical Engineering, Robotics, or a ...
New
AI / Embedded ML Engineer
Saratoga, CA · On-site
$145K - $190K/yr
... TinyML and Embedded Deployment • Optimize models for deployment on microcontrollers and edge processors such as ARM Cortex-M, RISC-V, and DSPs • Apply quantization, pruning, and knowledge ...
AI / Embedded ML Engineer
Saratoga, CA · On-site
$145K - $190K/yr
... TinyML and Embedded Deployment • Optimize models for deployment on microcontrollers and edge processors such as ARM Cortex-M, RISC-V, and DSPs • Apply quantization, pruning, and knowledge ...
AI / Embedded ML Engineer
Saratoga, CA · Hybrid
$145K - $190K/yr
... TinyML and Embedded Deployment Optimize models for deployment on microcontrollers and edge processors such as ARM Cortex-M, RISC-V, and DSPs Apply quantization, pruning, and knowledge distillation to ...
AI / Embedded ML Engineer
Saratoga, CA · Hybrid
$145K - $190K/yr
... TinyML and Embedded Deployment Optimize models for deployment on microcontrollers and edge processors such as ARM Cortex-M, RISC-V, and DSPs Apply quantization, pruning, and knowledge distillation to ...
AI / Embedded ML Engineer
Saratoga, CA · Hybrid
$145K - $190K/yr
... TinyML and Embedded Deployment ◦ Optimize models for deployment on microcontrollers and edge processors such as ARM Cortex-M, RISC-V, and DSPs ◦ Apply quantization, pruning, and knowledge ...
Quick apply
Apply Early
AI / Embedded ML Engineer
Saratoga, CA · Hybrid
$145K - $190K/yr
... TinyML and Embedded Deployment ◦ Optimize models for deployment on microcontrollers and edge processors such as ARM Cortex-M, RISC-V, and DSPs ◦ Apply quantization, pruning, and knowledge ...
Apply Early
Account Executive
Chicago, IL · On-site
Technical & Learning Agility Interest and willingness to learn concepts related to machine learning and tinyML. Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Account Executive
Chicago, IL · On-site
Technical & Learning Agility Interest and willingness to learn concepts related to machine learning and tinyML. Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Sr. Staff Embedded AI Engineer
$130K - $171K/yr
Company Description Renesas is seeking a Sr. Staff Embedded AI Engineer to develop advanced TinyML and embedded AI solutions targeting Renesas microcontroller and MPU platforms (RA, RL78, RX, RZ)
Sr. Staff Embedded AI Engineer
$130K - $171K/yr
Company Description Renesas is seeking a Sr. Staff Embedded AI Engineer to develop advanced TinyML and embedded AI solutions targeting Renesas microcontroller and MPU platforms (RA, RL78, RX, RZ)
Technical & Learning Agility Interest and willingness to learn concepts related to machine learning and tinyML. Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Technical & Learning Agility Interest and willingness to learn concepts related to machine learning and tinyML. Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Sr. Staff Embedded AI Engineer
Columbia, MD · On-site
$130K - $171K/yr
Company Description Renesas is seeking a Sr. Staff Embedded AI Engineer to develop advanced TinyML and embedded AI solutions targeting Renesas microcontroller and MPU platforms (RA, RL78, RX, RZ)
Quick apply
Apply Early
Sr. Staff Embedded AI Engineer
Columbia, MD · On-site
$130K - $171K/yr
Company Description Renesas is seeking a Sr. Staff Embedded AI Engineer to develop advanced TinyML and embedded AI solutions targeting Renesas microcontroller and MPU platforms (RA, RL78, RX, RZ)
Apply Early
Familiarity with TinyML, CMSIS libraries, or other embedded ML frameworks * Experience with embedded system architecture and designing control software frameworks Please note that, due to the high ...
Familiarity with TinyML, CMSIS libraries, or other embedded ML frameworks * Experience with embedded system architecture and designing control software frameworks Please note that, due to the high ...
Account Executive
San Clemente, CA · On-site
Technical & Learning Agility Interest and willingness to learn concepts related to machine learning and tinyML. Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Account Executive
San Clemente, CA · On-site
Technical & Learning Agility Interest and willingness to learn concepts related to machine learning and tinyML. Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Account Executive
Phoenix, AZ · On-site
Technical & Learning Agility Interest and willingness to learn concepts related to machine learning and tinyML. Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Account Executive
Phoenix, AZ · On-site
Technical & Learning Agility Interest and willingness to learn concepts related to machine learning and tinyML. Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Sr. Staff Embedded AI Engineer
Columbia, MD · On-site
$130K - $171K/yr
Company Description Renesas is seeking a Sr. Staff Embedded AI Engineer to develop advanced TinyML and embedded AI solutions targeting Renesas microcontroller and MPU platforms (RA, RL78, RX, RZ)
Sr. Staff Embedded AI Engineer
Columbia, MD · On-site
$130K - $171K/yr
Company Description Renesas is seeking a Sr. Staff Embedded AI Engineer to develop advanced TinyML and embedded AI solutions targeting Renesas microcontroller and MPU platforms (RA, RL78, RX, RZ)
Technical & Learning Agility Interest and willingness to learn concepts related to machine learning and tinyML. Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Technical & Learning Agility Interest and willingness to learn concepts related to machine learning and tinyML. Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Account Executive
San Clemente, CA · On-site
$130K/yr
Technical & Learning Agility • Interest and willingness to learn concepts related to machine learning and tinyML. • Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Account Executive
San Clemente, CA · On-site
$130K/yr
Technical & Learning Agility • Interest and willingness to learn concepts related to machine learning and tinyML. • Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Technical & Learning Agility Interest and willingness to learn concepts related to machine learning and tinyML. Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Technical & Learning Agility Interest and willingness to learn concepts related to machine learning and tinyML. Proficient in standard business tools, including Microsoft Office, Outlook, CRM ...
Senior Embedded Firmware Engineer, SmartSense (Boston, MA - Hybrid)
Boston, MA · On-site
$105K - $164K/yr
Interest in TinyML, edge inference, or embedded analytics. * Background in ultra-low-power design. * Experience working in regulated or compliance-driven environments. *Please note that we are unable ...
Senior Embedded Firmware Engineer, SmartSense (Boston, MA - Hybrid)
Boston, MA · On-site
$105K - $164K/yr
Interest in TinyML, edge inference, or embedded analytics. * Background in ultra-low-power design. * Experience working in regulated or compliance-driven environments. *Please note that we are unable ...
Nice to Have • Experience with Rust in embedded contexts. • Familiarity with TinyML or edge ML frameworks (TFLite Micro, Edge Impulse, ONNX Runtime). • Background in aerospace, satellite, or ...
Quick apply
Apply Early
Nice to Have • Experience with Rust in embedded contexts. • Familiarity with TinyML or edge ML frameworks (TFLite Micro, Edge Impulse, ONNX Runtime). • Background in aerospace, satellite, or ...
Apply Early
Lead Embedded Systems Software Engineer
$150K - $225K/yr
Familiarity with TinyML or edge ML frameworks (TFLite Micro, Edge Impulse, ONNX Runtime). Background in aerospace, satellite, or other safety-critical systems. Experience with model optimization ...
Lead Embedded Systems Software Engineer
$150K - $225K/yr
Familiarity with TinyML or edge ML frameworks (TFLite Micro, Edge Impulse, ONNX Runtime). Background in aerospace, satellite, or other safety-critical systems. Experience with model optimization ...
Lead Embedded Systems Software Engineer
Saratoga, CA · On-site
$150K - $225K/yr
Nice to Have • Experience with Rust in embedded contexts. • Familiarity with TinyML or edge ML frameworks (TFLite Micro, Edge Impulse, ONNX Runtime). • Background in aerospace, satellite, or ...
Lead Embedded Systems Software Engineer
Saratoga, CA · On-site
$150K - $225K/yr
Nice to Have • Experience with Rust in embedded contexts. • Familiarity with TinyML or edge ML frameworks (TFLite Micro, Edge Impulse, ONNX Runtime). • Background in aerospace, satellite, or ...
Tinyml information
What are the key skills and qualifications needed to thrive in the Tinyml position, and why are they important?
To excel in a TinyML role, you need expertise in embedded systems, machine learning, signal processing, and proficiency in programming languages like C/C++ and Python, often backed by a degree in computer engineering, electrical engineering, or computer science. Familiarity with TensorFlow Lite, microcontrollers (such as ARM Cortex-M), and deployment tools is typically required, along with relevant industry certifications. Effective problem-solving, teamwork, and strong communication skills are valuable for translating business needs into efficient, resource-constrained ML solutions. These capabilities are crucial for integrating intelligent models onto edge devices, where memory, power, and processing efficiency are paramount.
What is a TinyML job?
A TinyML job involves developing and deploying machine learning models on ultra-low-power devices like microcontrollers and edge sensors. Professionals in this field work on optimizing algorithms for efficiency, ensuring models run with minimal computational resources. Tasks typically include data preprocessing, model quantization, and performance optimization for embedded systems. TinyML engineers collaborate with hardware and software teams to create AI-driven solutions in IoT, healthcare, and industrial applications.
What are some common challenges faced in a TinyML position?
Professionals in TinyML often encounter challenges such as optimizing machine learning models to fit within the tight memory and processing constraints of microcontrollers and edge devices. Adapting algorithms for low power consumption without sacrificing performance requires creative problem-solving and a deep understanding of both hardware and software limitations. Additionally, collaboration with hardware engineers, data scientists, and product designers is frequent, making strong communication and cross-disciplinary teamwork essential. Overcoming these challenges is highly rewarding, as it leads to innovative solutions powering the next generation of smart, connected devices.
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What job categories do people searching Tinyml jobs look for? The top searched job categories for Tinyml jobs are:
$134K - $177K/yr
Full-time
Posted yesterday
Job description
Job Summary:
OVA.Work is seeking an Edge AI Engineer to design, develop, optimize, and deploy artificial intelligence and machine learning models on edge devices. The role focuses on building low-latency, power-efficient AI applications for various domains including IoT, robotics, and healthcare.
Responsibilities:
• Design, develop, and deploy AI/ML models for edge devices and embedded systems.
• Optimize deep learning models for low-latency, memory-efficient, and power-efficient inference.
• Convert and deploy models using frameworks such as TensorFlow Lite, ONNX Runtime, TensorRT, and OpenVINO.
• Develop AI applications for computer vision, speech processing, sensor analytics, and real-time decision-making.
• Integrate AI models with embedded hardware, IoT devices, and edge computing platforms.
• Collaborate with hardware engineers, firmware developers, software engineers, and data scientists to deliver end-to-end edge AI solutions.
• Develop and optimize inference pipelines for GPUs, NPUs, TPUs, DSPs, and microcontrollers.
• Perform model benchmarking, profiling, quantization, pruning, and performance tuning.
• Implement secure model deployment, over-the-air (OTA) updates, and device lifecycle management.
• Build APIs and edge services for AI-enabled applications.
• Monitor deployed edge AI systems and continuously improve performance, reliability, and resource utilization.
• Stay current with advancements in edge computing, embedded AI, AI accelerators, and TinyML technologies.
Qualifications:
Required:
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Electronics, Embedded Systems, Electrical Engineering, Robotics, or a related field.
• 3–8+ years of experience in AI/ML, embedded systems, edge computing, or software engineering.
• Strong proficiency in Python and C/C++.
• Experience developing and deploying machine learning and deep learning models.
• Knowledge of embedded Linux, real-time operating systems (RTOS), and IoT architectures.
• Experience with model optimization and deployment frameworks.
• Familiarity with computer vision, signal processing, or sensor fusion applications.
• Strong understanding of software engineering principles, debugging, and performance optimization.
Preferred:
• Experience with NVIDIA Jetson, Raspberry Pi, Qualcomm AI platforms, Client Movidius, Google Coral, or similar edge hardware.
• Knowledge of TinyML and microcontroller-based AI deployments.
• Experience with robotics, autonomous systems, or industrial automation.
• Familiarity with MLOps for edge deployments and fleet management.
• Experience with cloud-edge integration and edge orchestration platforms.
• Relevant AI, embedded systems, or cloud certifications.
Company:
OVA is the most advanced Automated, Intelligent, intuitive On-boarding platform for Staffing Firms of all sizes. Founded in 2018, the company is headquartered in Alpharetta, USA, with a team of 51-200 employees. The company is currently Growth Stage.
OVA.Work is seeking an Edge AI Engineer to design, develop, optimize, and deploy artificial intelligence and machine learning models on edge devices. The role focuses on building low-latency, power-efficient AI applications for various domains including IoT, robotics, and healthcare.
Responsibilities:
• Design, develop, and deploy AI/ML models for edge devices and embedded systems.
• Optimize deep learning models for low-latency, memory-efficient, and power-efficient inference.
• Convert and deploy models using frameworks such as TensorFlow Lite, ONNX Runtime, TensorRT, and OpenVINO.
• Develop AI applications for computer vision, speech processing, sensor analytics, and real-time decision-making.
• Integrate AI models with embedded hardware, IoT devices, and edge computing platforms.
• Collaborate with hardware engineers, firmware developers, software engineers, and data scientists to deliver end-to-end edge AI solutions.
• Develop and optimize inference pipelines for GPUs, NPUs, TPUs, DSPs, and microcontrollers.
• Perform model benchmarking, profiling, quantization, pruning, and performance tuning.
• Implement secure model deployment, over-the-air (OTA) updates, and device lifecycle management.
• Build APIs and edge services for AI-enabled applications.
• Monitor deployed edge AI systems and continuously improve performance, reliability, and resource utilization.
• Stay current with advancements in edge computing, embedded AI, AI accelerators, and TinyML technologies.
Qualifications:
Required:
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Electronics, Embedded Systems, Electrical Engineering, Robotics, or a related field.
• 3–8+ years of experience in AI/ML, embedded systems, edge computing, or software engineering.
• Strong proficiency in Python and C/C++.
• Experience developing and deploying machine learning and deep learning models.
• Knowledge of embedded Linux, real-time operating systems (RTOS), and IoT architectures.
• Experience with model optimization and deployment frameworks.
• Familiarity with computer vision, signal processing, or sensor fusion applications.
• Strong understanding of software engineering principles, debugging, and performance optimization.
Preferred:
• Experience with NVIDIA Jetson, Raspberry Pi, Qualcomm AI platforms, Client Movidius, Google Coral, or similar edge hardware.
• Knowledge of TinyML and microcontroller-based AI deployments.
• Experience with robotics, autonomous systems, or industrial automation.
• Familiarity with MLOps for edge deployments and fleet management.
• Experience with cloud-edge integration and edge orchestration platforms.
• Relevant AI, embedded systems, or cloud certifications.
Company:
OVA is the most advanced Automated, Intelligent, intuitive On-boarding platform for Staffing Firms of all sizes. Founded in 2018, the company is headquartered in Alpharetta, USA, with a team of 51-200 employees. The company is currently Growth Stage.