ZipRecruiter

Log In

2

Remote Embedded Systems Engineer Jobs in Chesapeake, VA

Ztek Consulting INC

AWS DevOPS/SRE Engineer

Norfolk, VA · Remote

$58.25 - $77.50/hr

AWS DevOPS/SRE Engineer REMOTE Top Skills Required : Devops Eng with strong AWS experience - DevOps ... Experience in Linux system administration DevOps / SRE Expertise * Strong understanding of DevOps ...

Stantec

Fire Protection Engineer (Remote or Hybrid)

Hampton, VA · On-site +1

$80K - $108K/yr

We value flexibility-remote or hybrid work options may be available depending on the candidate and ... Perform calculations to analyze and design engineering system components using company standard ...

ASEC

Network Engineer

Virginia Beach, VA · On-site +1

$135K - $150K/yr

Support connectivity between live platforms, simulators, command centers, and remote training ... A bachelor's degree in Cybersecurity, Data Science, Information Systems or Information Technology ...

Commence

Full Stack Software Engineer

Virginia Beach, VA · Remote

$105K - $135K/yr

Enhance and maintain existing systems by identifying and addressing areas for improvement ... This is a remote position. Candidates must be able to sit, read, work on a computer, and watch a ...

Commence

Sr Site Reliability Engineer

Virginia Beach, VA · On-site +1

$145K - $175K/yr

This role is built for someone who thrives when systems are under pressure and who treats an outage ... This is a remote position. While performing the duties of this job, the employee regularly works in ...

previous pagenext page

Showing results 21-40

All JobsEmbedded Systems Engineer JobsRemote Embedded Systems Engineer JobsRemote Embedded Systems Engineer Jobs in Chesapeake, VA

Remote Embedded Systems Engineer information

See Chesapeake, VA salary details

$60.7K

$133.3K

$186.5K

How much do remote embedded systems engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for remote embedded systems engineer in Chesapeake, VA is $133,319.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,300.00 and $158,800.00 per year, depending on experience, location, and employer.

What is a remote embedded systems engineer?

A Remote Embedded Systems Engineer is a professional who designs, develops, and maintains embedded systems—specialized computing systems that perform dedicated functions within larger mechanical or electrical systems—while working remotely. These engineers work with hardware and software, often programming microcontrollers or processors, to create solutions for products like smart devices, automotive systems, or industrial machines. Their remote role means they collaborate virtually with teams, using tools for code development, debugging, and communication. Strong knowledge of C/C++, Linux, and real-time operating systems (RTOS) is often required. Remote Embedded Systems Engineers play a crucial role in the growing fields of IoT, automation, and smart technologies.

What are the key skills and qualifications needed to thrive as a remote embedded systems engineer, and why are they important?

To thrive as a Remote Embedded Systems Engineer, you need a solid background in electrical engineering, proficiency in C/C++ programming, and experience with embedded hardware and software design. Familiarity with development tools such as debuggers, oscilloscopes, version control systems (like Git), and RTOS platforms, as well as certifications like Certified Embedded Systems Engineer, are commonly required. Strong problem-solving abilities, self-motivation, and effective remote communication skills set top candidates apart in this role. These skills are essential for developing reliable, high-performance embedded solutions while collaborating efficiently in distributed teams.

How do remote embedded systems engineers typically collaborate with hardware teams when working off-site?

Remote Embedded Systems Engineers often collaborate with hardware teams through video conferencing, collaborative design tools, and remote access to development boards. Regular virtual meetings are scheduled for project updates, troubleshooting, and aligning on hardware-software integration requirements. To stay effective, engineers may use remote debugging tools and sometimes ship prototype hardware to their home office, ensuring they can test and validate firmware in real time. Clear documentation and proactive communication are essential for overcoming the physical distance and ensuring successful project outcomes.

What is the difference between Remote Embedded Systems Engineer vs Remote Firmware Developer?

AspectRemote Embedded Systems EngineerRemote Firmware Developer
Required CredentialsBachelor's in Electrical Engineering, Computer Engineering, or related field; knowledge of embedded C/C++Bachelor's in Computer Science, Electrical Engineering; proficiency in embedded C, assembly, and RTOS
Work EnvironmentDesigning and testing hardware-software integration, often in R&D labs or remote setupsDeveloping low-level code for hardware devices, often in embedded systems or IoT projects
Employer & Industry UsageElectronics, automotive, aerospace, IoT companiesConsumer electronics, industrial automation, IoT device manufacturers

While both roles involve working with embedded hardware and software, the Remote Embedded Systems Engineer typically focuses on system design, integration, and testing, whereas the Remote Firmware Developer specializes in writing low-level firmware code for specific hardware components. Both roles require similar technical skills and often overlap in industry applications.

What are the most commonly searched types of Embedded Systems Engineer jobs in Chesapeake, VA?

The most popular types of Embedded Systems Engineer jobs in Chesapeake, VA are:

What are popular job titles related to Remote Embedded Systems Engineer jobs in Chesapeake, VA?

For Remote Embedded Systems Engineer jobs in Chesapeake, VA, the most frequently searched job titles are:

What job categories do people searching Remote Embedded Systems Engineer jobs in Chesapeake, VA look for?

The top searched job categories for Remote Embedded Systems Engineer jobs in Chesapeake, VA are:

What cities near Chesapeake, VA are hiring for Remote Embedded Systems Engineer jobs?

Cities near Chesapeake, VA with the most Remote Embedded Systems Engineer job openings:

Remote Embedded Systems Engineer jobs near you
Infographic showing various Remote Embedded Systems Engineer job openings in Chesapeake, VA as of August 2026, with employment types broken down into 85% Full Time, 9% Part Time, 5% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $133,319 per year, or $64.1 per hour.

Senior MLOps & Generative AI Engineer - Remote

Sentara Healthcare

Virginia Beach, VA • On-site, Remote

$99K - $136K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 15 days ago

Sentara Health rating

6.7

Company rating: 6.7 out of 10

Based on 412 frontline employees who took The Breakroom Quiz

531st of 888 rated healthcare providers

Job description

City/State
Virginia Beach, VA
Work Shift
Multiple shifts available
Overview:
Sentara is hiring a Senior MLOps & Generative AI Engineer!
This position is fully remote!
Selected candidates would be required to be onsite for final round of team interview
Candidates must reside in one of the following states:
Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington, West Virginia, Wisconsin, or Wyoming.
Overview
We are seeking a highly skilled and experienced Senior MLOps & Generative AI Engineer to join our growing AI organization and help advance current and future initiatives applying machine learning, deep learning, NLP, and Generative AI technologies to improve healthcare outcomes and operational excellence.
This role combines two critical focus areas:
  • MLOps Engineering - building and scaling enterprise-grade ML infrastructure, deployment pipelines, observability, governance, and automation capabilities.
  • Generative AI Engineering - designing, architecting, deploying, and optimizing secure, production-ready GenAI applications and platforms leveraging LLMs, RAG architectures, vector databases, prompt orchestration, and AI evaluation frameworks.

As a Senior Engineer, you will partner closely with AI Scientists, Data Engineers, Software Engineers, Architects, and Product teams to operationalize AI/ML and Generative AI solutions at enterprise scale. You will play a key role in shaping the organization's AI platform strategy, driving best practices, and delivering scalable, secure, and reliable AI systems in production healthcare environments.
Key Responsibilities
MLOps Engineering Responsibilities
  • Design, build, and maintain scalable ML infrastructure and pipelines supporting model training, deployment, monitoring, governance, and lifecycle management.
  • Develop and optimize CI/CD pipelines for machine learning and AI workloads across development, staging, and production environments.
  • Build reusable ML platform capabilities including feature stores, model registries, experimentation frameworks, artifact management, and deployment automation.
  • Implement scalable orchestration and workflow solutions for batch and real-time ML inference workloads.
  • Create robust monitoring systems to measure model performance, detect model drift, monitor data quality, and ensure production reliability.
  • Develop automation tools and self-service capabilities to improve the efficiency, scalability, and reliability of MLOps processes.
  • Collaborate with Data Scientists and Software Engineers to streamline the ML lifecycle from experimentation through enterprise production deployment.
  • Apply software engineering best practices to AI/ML systems including testing, observability, resiliency, security, versioning, and infrastructure-as-code.
  • Identify gaps and improvement opportunities within the organization's ML platform ecosystem and architect scalable solutions to address them.
  • Support enterprise AI governance, compliance, auditability, and model risk management requirements.
  • Ensure platform scalability, reliability, security, and operational excellence across AI/ML systems.

Generative AI Engineering Responsibilities
  • Lead the architecture, design, and deployment of enterprise Generative AI solutions leveraging LLMs, foundation models, and agentic AI systems.
  • Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases, embeddings, semantic search, reranking, and retrieval optimization strategies.
  • Build scalable LLM orchestration frameworks using technologies such as LangChain, LlamaIndex, Semantic Kernel, or equivalent frameworks.
  • Develop advanced prompt engineering strategies, prompt chaining, context management, and agent workflows to improve LLM accuracy and reliability.
  • Evaluate and implement fine-tuning, parameter-efficient tuning, and prompt-based optimization approaches for domain-specific use cases.
  • Build AI evaluation and benchmarking frameworks to measure hallucination rates, response quality, grounding accuracy, toxicity, bias, latency, and business performance metrics.
  • Implement AI safety guardrails, governance controls, content filtering, and responsible AI practices for enterprise healthcare environments.
  • Design scalable GenAI APIs and microservices supporting high-throughput enterprise AI applications.
  • Optimize GenAI systems for cost, latency, throughput, and inference performance across cloud and hybrid environments.
  • Integrate enterprise data sources, healthcare systems, and knowledge repositories into secure GenAI workflows.
  • Research and evaluate emerging GenAI technologies, open-source frameworks, and foundation models to drive innovation and continuous improvement.
  • Develop architecture diagrams, technical roadmaps, implementation strategies, and executive-level documentation for enterprise AI initiatives.
  • Collaborate with cybersecurity, compliance, and infrastructure teams to ensure secure and compliant deployment of GenAI solutions involving PHI and sensitive healthcare data.
  • Contribute to the development of AI platform standards, reusable GenAI accelerators, templates, and engineering best practices.

Required Qualifications
  • 5+ years of experience building and deploying production software, ML systems, or AI platforms.
  • 1+ years of hands-on experience building production Generative AI or LLM-based applications.
  • Strong programming skills in Python and experience with software engineering best practices.
  • Experience with major deep learning and LLM frameworks such as PyTorch, Hugging Face Transformers, TensorFlow, or equivalent.
  • Hands-on experience implementing RAG architectures, vector search, embeddings, prompt engineering, and LLM orchestration frameworks.
  • Experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, Milvus, or equivalent technologies.
  • Experience deploying AI/ML systems in cloud environments including AWS, Azure, or GCP.
  • Strong understanding of APIs, distributed systems, microservices, and scalable backend architectures.
  • Experience with Kubernetes, containerization, orchestration, and cloud-native infrastructure.
  • Experience implementing CI/CD pipelines, infrastructure automation, and MLOps best practices.
  • Experience building monitoring, observability, and alerting solutions for ML and AI systems.
  • Strong understanding of AI/ML lifecycle management, governance, model versioning, and production operations.
  • Experience designing secure, scalable, production-ready AI platforms and services.
  • Strong communication and collaboration skills with the ability to work across technical and business teams.

Preferred Qualifications
  • Previous experience implementing Generative AI and MLOps solutions within healthcare environments.
  • Experience working with EPIC or healthcare interoperability platforms.
  • Understanding of HIPAA, PHI handling, healthcare compliance, and responsible AI practices.
  • Experience with AI governance frameworks, LLM evaluation methodologies, and AI safety tooling.
  • Experience with GPU infrastructure optimization and scalable inference architectures.
  • Familiarity with multi-agent AI systems and autonomous workflows.
  • Experience with event-driven architectures, streaming pipelines, and real-time inference systems.
  • Exposure to model fine-tuning techniques including LoRA, PEFT, RLHF, or domain adaptation strategies.
  • Experience with enterprise AI platform architecture and internal developer platforms.
  • Prior experience mentoring engineers and leading technical initiatives.

Education
  • 5+ years of relevant experience with a degree (Required)

or
  • 7+ years of relevant experience without a degree (Required)
  • Experience in lieu of Bachelor's Degree.

Certification/Licensure
  • No specific certification or licensure requirements

Experience
  • 5 to 7 years of relevant experience

We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for Full Time employment is: 91,416.00 - 152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities.
Keywords: Talroo-IT, MLOps, Gen AI, LLM, AWS, Azure, GCP, AI/ML, Python, PyTorch, Hugging Face Transformers, TensorFlow, RAG, EPIC, HIPAA, AI Governance
Benefits: Caring For Your Family and Your Career
• Medical, Dental, Vision plans
• Adoption, Fertility and Surrogacy Reimbursement up to 10,000
• Paid Time Off and Sick Leave
• Paid Parental & Family Caregiver Leave
• Emergency Backup Care
• Long-Term, Short-Term Disability, and Critical Illness plans
• Life Insurance
• 401k/403B with Employer Match
• Tuition Assistance - 5,250/year and discounted educational opportunities through Guild Education
• Student Debt Pay Down - 10,000
• Pet Insurance
• Legal Resources Plan
• Colleagues have the opportunity to earn an annual discretionary bonus if established system and employee eligibility criteria is met.
Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves.
In support of our mission "to improve health every day," this is a tobacco-free environment.
For positions that are available as remote work, Sentara Health employs associates in the following states:
Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.

What Sentara Health employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply