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Remote Computer Chip Engineer Jobs (NOW HIRING)

ASIC/SOC CAD Engineer

Mountain View, CA · On-site +1

$175K - $362K/yr

MatX is seeking a Physical Design CAD Engineer to join our team as we create best-in-class silicon ... Remote Perks We work remotely Monday & Friday, supported by home-tech setup, and remote wifi ...

AXIS cameras include the ARTPEC-8 chip with an onboard AI inference engine (Larod) and support ... based computer vision systems. * Remote Troubleshooting and Fleet Management: track record of ...

AXIS cameras include the ARTPEC-8 chip with an onboard AI inference engine (Larod) and support ... based computer vision systems. * Remote Troubleshooting and Fleet Management: track record of ...

Position: CAD Engineer -- ScreenSpot Plus (Screenshot Capture & UI Annotation) Type: Contract ... Remote Role Responsibilities * Capture high-quality screenshots of professional CAD software during ...

Senior Firmware Security Engineer

Austin, TX · On-site +1

$118K - $156K/yr

... from chip architecture to system performance at scale. Cornelis Networks delivers the world ... Bachelor's orMaster's degree in Computer Engineering, Electrical Engineering, Computer Science, or ...

Senior Software Engineer - SAI/SDK

Austin, TX · On-site +1

$121K - $160K/yr

... from chip architecture to system performance at scale. Cornelis Networks delivers the world ... This is a remote position for employees residing within the United States. We offer a competitive ...

Senior Software Engineer - SAI/SDK

Austin, TX · On-site +1

$121K - $160K/yr

... from chip architecture to system performance at scale. Cornelis Networks delivers the world ... This is a remote position for employees residing within the United States. We offer a competitive ...

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Remote Computer Chip Engineer information

See salary details

$48.5K

$121.5K

$137.5K

How much do remote computer chip engineer jobs pay per year?

As of Jun 22, 2026, the average yearly pay for remote computer chip engineer in the United States is $121,515.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $131,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Computer Chip Engineer, and why are they important?

To thrive as a Remote Computer Chip Engineer, you need a strong background in electrical engineering, digital/analog circuit design, and semiconductor fundamentals, typically supported by a relevant degree. Familiarity with CAD tools like Cadence or Synopsys, experience with HDL languages (such as Verilog or VHDL), and knowledge of simulation and verification systems are essential. Excellent problem-solving, self-motivation, and effective remote communication skills set top engineers apart in virtual teams. These competencies ensure high-quality chip development, efficient collaboration, and successful project delivery in a remote work environment.

What does a Remote Computer Chip Engineer do?

A Remote Computer Chip Engineer designs, develops, tests, and optimizes microchips and integrated circuits while working from a remote location. They use specialized software tools to create blueprints, simulate chip behavior, and collaborate with other engineers online. Their work is crucial in developing faster, more efficient processors and electronic devices. By working remotely, they leverage digital communication and project management tools to coordinate with teams around the world.

What are some common challenges faced by Remote Computer Chip Engineers, and how can they be addressed?

Remote Computer Chip Engineers often face challenges related to effective collaboration, particularly when working across different time zones or with team members in various locations. Communication about design updates, debugging, and hardware testing can require extra coordination. To address these issues, teams typically use robust project management tools, regular video meetings, and clear documentation practices. Establishing strong communication channels and proactively sharing progress help ensure everyone stays aligned and projects move forward efficiently.
More about Remote Computer Chip Engineer jobs
What cities are hiring for Remote Computer Chip Engineer jobs? Cities with the most Remote Computer Chip Engineer job openings:
What are the most commonly searched types of Computer Chip Engineer jobs? The most popular types of Computer Chip Engineer jobs are:
What states have the most Remote Computer Chip Engineer jobs? States with the most job openings for Remote Computer Chip Engineer jobs include:
Infographic showing various Remote Computer Chip Engineer job openings in the United States as of June 2026, with employment types broken down into 83% Full Time, 11% Part Time, and 6% Contract. Highlights an 6% In-person, and 94% Remote job distribution, with an average salary of $121,515 per year, or $58.4 per hour.
AI Infrastructure Engineer - Emerging Technologies

AI Infrastructure Engineer - Emerging Technologies

Cologix, Inc.

Remote

$110K - $144K/yr

Full-time

Posted 6 days ago


Job description

Job Summary:
Cologix, Inc. is a leading North America network-neutral interconnection and hyperscale edge data center company. They are seeking an AI Infrastructure Engineer – Emerging Technologies to support the evaluation, design, and development of next-generation AI-ready data center infrastructure strategies, bridging emerging AI technologies with practical implementation across various engineering and operational functions.
Responsibilities:
• Support the VP of Technology Engineering & Innovation in evaluating emerging AI infrastructure technologies and future-ready data center strategies.
• Analyze AI workload characteristics including:
• Training vs. inference workloads
• GPU utilization patterns
• Dynamic workload fluctuations
• Rack-level power variability
• Networking and latency requirements
• Assess implications of AI workload behavior on infrastructure resiliency, scalability, efficiency, and operational design.
• Develop technical recommendations and infrastructure strategies supporting future AI deployments.
• Analyze current and future AI compute platforms including NVIDIA GPU architectures, ARM-based platforms, custom AI accelerators and ASICs, optical networking and switching technologies, and emerging hyperscaler-designed AI chips.
• Evaluate implications of evolving chip architectures on rack density, power consumption, cooling requirements, electrical distribution, mechanical infrastructure, space planning, and future development standards.
• Model current and future AI rack power density trends including existing high-density deployments (50–120 kW), near-term AI deployments (150–300+ kW), and future ultra-dense AI cluster scenarios.
• Assess long-term impacts of emerging chip architectures on energy efficiency and future data center design and development standards.
• Support conceptual and detailed design efforts for AI-ready data center infrastructure.
• Assist in developing long-term infrastructure roadmaps for high-density AI deployments, liquid cooling adoption, modular infrastructure strategies, utility coordination, grid-parallel and microgrid solutions, and future AI campus development.
• Evaluate implications of AI infrastructure evolution on greenfield developments, existing facility retrofits, construction methodologies, scalability, and future campus master planning.
• Collaborate with engineering, development, and construction teams to develop scalable AI-ready infrastructure standards and deployment models.
• Collaborate closely with the Energy Strategy Team to evaluate utility constraints, interconnection requirements, grid limitations, dynamic load fluctuation impacts, power quality and resiliency considerations, and onsite generation and distributed energy solutions.
• Support analysis of grid-parallel and islanded microgrid architectures, fuel cells, Battery Energy Storage Systems (BESS), bridge power solutions, natural gas generation, and renewable integration opportunities.
• Evaluate implications of AI workloads on substation development, transmission planning, utility coordination, and energy efficiency and PUE optimization.
• Assess how future AI compute growth will influence utility planning and power infrastructure strategies.
• Analyze current and emerging thermal management solutions including air cooling, direct-to-chip liquid cooling, immersion cooling, rear-door heat exchangers, and hybrid cooling architectures.
• Assess implications of ultra-high-density AI deployments on mechanical system design, water usage, cooling scalability, heat rejection strategies, thermal resiliency, and future cooling infrastructure standards.
• Evaluate cooling technologies and infrastructure requirements as AI rack densities continue to increase.
• Interface directly with technology vendors, OEMs, utilities, and strategic partners across power generation, UPS systems, electrical infrastructure, cooling technologies, liquid cooling platforms, AI compute infrastructure, and networking and optical interconnect technologies.
• Lead technical assessments of next-generation technologies with respect to reliability, scalability, energy efficiency, sustainability, AI workload performance, construction complexity, and operational resiliency.
• Support proof-of-concept initiatives, pilot deployments, and technology benchmarking efforts.
• Develop executive-level recommendations regarding adoption of emerging AI infrastructure technologies and strategic engineering standards.
• Collaborate with design engineering, construction, operations, energy strategy, procurement, utilities, technology partners, and external engineering firms and consultants.
• Support strategic planning initiatives and executive-level technical presentations.
• Assist in developing future infrastructure standards and innovation roadmaps for AI-enabled data center platforms.
Qualifications:
Required:
• Bachelor's degree in Electrical Engineering, Mechanical Engineering, Computer Engineering, Computer Science, Data Center Engineering, or a related technical discipline.
• 5+ years of experience in one or more of the following: data center infrastructure, AI/HPC infrastructure, power systems engineering, cooling technologies, or advanced infrastructure engineering.
• Strong understanding of emerging AI compute technologies and infrastructure implications.
• Ability to analyze complex technical systems and translate findings into actionable engineering and infrastructure strategies.
Preferred:
• Master's degree and/or PhD in Engineering, Computer Science, Data Science, Energy Systems, or a related technical field.
• Experience with hyperscale or colocation data center environments.
• Knowledge of GPU infrastructure and AI workload behavior.
• Familiarity with utility coordination and energy systems.
• Understanding of high-density cooling technologies.
• Experience supporting large-scale infrastructure development projects.
• PE license or equivalent advanced technical credentials.
Company:
At Cologix, our mission is to cultivate a sustainable digital world that connects people, businesses and communities. Founded in 2010, the company is headquartered in Denver, USA, with a team of 501-1000 employees. The company is currently Growth Stage.