... computing frameworks, and our enterprise cloud infrastructure. What you will do: * End-to-End ... Mentor junior and mid-level engineers on the team. * Perform additional duties as assigned. What ...
... computing frameworks, and our enterprise cloud infrastructure. What you will do: * End-to-End ... Mentor junior and mid-level engineers on the team. * Perform additional duties as assigned. What ...
... computing frameworks, and our enterprise cloud infrastructure. What you will do: * End-to-End ... Mentor junior and mid-level engineers on the team. * Perform additional duties as assigned. What ...
... computing frameworks, and our enterprise cloud infrastructure. What you will do: * End-to-End ... Mentor junior and mid-level engineers on the team. * Perform additional duties as assigned. What ...
... computing frameworks, and our enterprise cloud infrastructure. What you will do: * End-to-End ... Mentor junior and mid-level engineers on the team. * Perform additional duties as assigned. What ...
... computing frameworks, and our enterprise cloud infrastructure. What you will do: * End-to-End ... Mentor junior and mid-level engineers on the team. * Perform additional duties as assigned. What ...
... computing frameworks, and our enterprise cloud infrastructure. What you will do: * End-to-End ... Mentor junior and mid-level engineers on the team. * Perform additional duties as assigned. What ...
... computing frameworks, and our enterprise cloud infrastructure. What you will do: * End-to-End ... Mentor junior and mid-level engineers on the team. * Perform additional duties as assigned. What ...
... computing frameworks, and our enterprise cloud infrastructure. What you will do: * End-to-End ... Mentor junior and mid-level engineers on the team. * Perform additional duties as assigned. What ...
... computing frameworks, and our enterprise cloud infrastructure. What you will do: * End-to-End ... Mentor junior and mid-level engineers on the team. * Perform additional duties as assigned. What ...
Embedded Systems Engineer IV, R&D
Buffalo, NY · On-site
$139K - $174K/yr
... computing frameworks, and our enterprise cloud infrastructure. What you will do: * End-to-End ... Mentor junior and mid-level engineers on the team. * Perform additional duties as assigned. What ...
Embedded Systems Engineer IV, R&D
Buffalo, NY · On-site
$139K - $174K/yr
... computing frameworks, and our enterprise cloud infrastructure. What you will do: * End-to-End ... Mentor junior and mid-level engineers on the team. * Perform additional duties as assigned. What ...
... high-level commentary * Understanding of and ability to leverage: * Cloud-based computing ... Demonstrated ability to engage and partner at mid to senior leadership levels; Established ...
... high-level commentary * Understanding of and ability to leverage: * Cloud-based computing ... Demonstrated ability to engage and partner at mid to senior leadership levels; Established ...
Mid Level Neuromorphic Computing information
See Lancaster, NY salary details
$10.5K - $19.4K
0% of jobs
$19.4K - $28.3K
0% of jobs
$28.3K - $37.2K
0% of jobs
$37.2K - $46.1K
0% of jobs
$46.1K - $55K
0% of jobs
$61.2K is the 25th percentile. Wages below this are outliers.
$55K - $63.9K
36% of jobs
$63.9K - $72.8K
0% of jobs
$72.8K - $81.7K
0% of jobs
The median wage is $85.2K / yr.
$81.7K - $90.6K
36% of jobs
$90.6K - $99.5K
0% of jobs
$100.6K is the 75th percentile. Wages above this are outliers.
$99.5K - $108.3K
29% of jobs
$10.5K
$83.1K
$108.3K
How much do mid level neuromorphic computing jobs pay per year?
As of Aug 12, 2026, the average yearly pay for mid level neuromorphic computing in Lancaster, NY is $83,095.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,500.00 and $103,100.00 per year, depending on experience, location, and employer.
What is a mid level neuromorphic computing professional?
Mid level neuromorphic computing professionals are specialists with several years of experience who design, develop, and optimize hardware and software systems inspired by the structure and function of the human brain. They typically work on building and programming neuromorphic chips, developing algorithms that mimic neural processes, and integrating these systems into real-world applications such as robotics or edge computing. Their expertise bridges neuroscience, computer engineering, and artificial intelligence, and they often collaborate with interdisciplinary teams to advance brain-inspired computing technologies.
What are some common challenges faced by professionals in mid level neuromorphic computing roles, and how can they be addressed?
Professionals in mid-level neuromorphic computing roles often encounter challenges such as integrating novel hardware with existing software systems, managing the complexity of neural-inspired algorithms, and keeping pace with rapid advancements in the field. Collaborating closely with multidisciplinary teams—including hardware engineers, data scientists, and neuroscientists—can help address these challenges. Additionally, staying updated on the latest research and industry trends, as well as participating in collaborative projects, can enhance problem-solving skills and foster innovation in this evolving area.
What is the difference between Mid Level Neuromorphic Computing vs Mid Level Machine Learning Engineer?
| Aspect | Mid Level Neuromorphic Computing | Mid Level Machine Learning Engineer |
|---|---|---|
| Required Credentials | Bachelor's in Computer Science, Electrical Engineering, or related field; knowledge of neuromorphic hardware | Bachelor's in Computer Science, Data Science, or related; experience with ML frameworks |
| Work Environment | Research labs, hardware development, AI hardware companies | Tech companies, startups, data-driven organizations |
| Industry Usage | AI hardware, neuromorphic chip design, cognitive computing | Software development, AI applications, data analysis |
Mid Level Neuromorphic Computing professionals focus on hardware and cognitive architectures inspired by the brain, often working with specialized hardware and research teams. In contrast, Mid Level Machine Learning Engineers develop algorithms and models primarily in software to solve data-driven problems. Both roles require a strong technical background but differ in their focus on hardware versus software applications.
What are the key skills and qualifications needed to thrive as a mid level neuromorphic computing engineer?
To thrive as a Mid Level Neuromorphic Computing Engineer, you need a solid background in computer engineering, neuroscience, and machine learning, usually supported by a relevant degree and experience with neural network architectures. Familiarity with tools like Python, MATLAB, TensorFlow, and simulation platforms such as NEST or SpiNNaker, along with knowledge of specialized hardware, is typically required. Strong problem-solving, collaboration, and communication skills help you innovate and effectively share complex ideas with multidisciplinary teams. These skills and qualifications are crucial for developing advanced neuromorphic systems that bridge neuroscience and AI, pushing the boundaries of efficient computing.
What cities near Lancaster, NY are hiring for Mid Level Neuromorphic Computing jobs? Cities near Lancaster, NY with the most Mid Level Neuromorphic Computing job openings:
Job description
Who we are looking for:
As an Engineer IV, Embedded Systems within the R&D team, you will serve as a technical anchor for our next-generation hardware platforms. You will design, develop, and optimize high-performance software running on a variety of embedded systems—ranging from single-board computers and edge AI compute modules to custom ARM architecture.
This role requires a unique blend of scrappy, proof-of-concept rapid prototyping and disciplined, production-grade software engineering. You will own the software lifecycle for new devices, ensuring seamless integration between low-level hardware, sensors, edge computing frameworks, and our enterprise cloud infrastructure.
What you will do:
- End-to-End Development: Architect, implement, and maintain embedded software from initial conceptual prototypes to ruggedized, scalable, enterprise-level production code.
- Platform Ownership: Develop and optimize firmware and middleware on platforms including Raspberry Pi, NVIDIA Jetson, and ARM-based System-on-Modules (SOMs).
- Sensor & Peripheral Integration: Write and debug low-level drivers and interfaces for a diverse ecosystem of peripherals, cameras, and environmental sensors via protocols such as I2C, SPI, UART, USB, and PCIe.
- Edge Intelligence & Compute: Optimize software on compute-constrained edge devices, including leveraging hardware acceleration (e.g., CUDA, TensorRT on Jetson platforms) for real-time data processing and computer vision pipelines.
- System Stability & Lifecycle: Design robust fault-detection, automated recovery mechanisms, and secure over-the-air (OTA) firmware update systems to ensure maximum field stability.
- Cross-Functional Collaboration: Partner closely with hardware/electrical engineers, mechanical designers, and cloud backend teams to define system architectures and interfaces.
- Mentorship & Standards: Drive code quality through rigorous code reviews, automated testing, and comprehensive documentation. Mentor junior and mid-level engineers on the team.
- Perform additional duties as assigned.
What you will need:
- Ability to read, write, speak and understand English.
- BS degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field (or equivalent practical experience).
- 6+ years’ Professional experience in embedded software development, with a proven track record of shipping commercial or industrial hardware products
- Expert-level proficiency in C and C++; strong scripting skills in Python or Bash for testing and automation.
- OS Expertise: Deep experience developing within Embedded Linux environments (including kernel configuration, device tree modification, and custom driver development).
- Hands-on experience building applications on Raspberry Pi (Linux/Debian) and NVIDIA Jetson (JetPack ecosystem).
- Solid understanding of hardware communication protocols: SPI, I2C, UART, CAN bus, USB.
- Experience interfacing with high-resolution image sensors, cameras, or specialized sensors.
- Proficiency with modern software engineering tools: Git, CMake, Docker, and CI/CD pipelines tailored for embedded targets.
- Familiarity with networking stacks and IoT communication protocols (TCP/IP, UDP, MQTT, gRPC).
- Comfortable utilizing lab equipment like oscilloscopes, logic analyzers, and multimeters to debug hardware/software boundary issues.
- Expert in version control systems including trunk-based development, multiple release planning, cherry picking, and rebase.
- Nice to Have Technical Competencies
- Experience with custom Linux distribution builders like Yocto Project or Buildroot.
- Familiarity with real-time operating systems (RTOS) or bare-metal ARM development.
- Experience deploying or optimizing machine learning models at the edge.
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