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Remote Measurement Engineer Jobs in Virginia (NOW HIRING)

Maximus

Database Engineer

VA · On-site +1

General information Job Posting Title Database Engineer Date Tuesday, June 9, 2026 City Remote ... and compliance measures to maintain system integrity. - Collaborate with infrastructure ...

GFT.

Senior Site/Civil Engineer

Roanoke, VA · On-site +1

$125K - $160K/yr

Louis, MO or Marlton, NJ This can be a remote position for the right candidate. * Develop projects ... We measure our success by the strength of our relationships - that's why we're the employer of ...

iDirect GOVERNMENT

Senior FPGA Engineer

Herndon, VA · On-site +1

$91K - $159K/yr

This position is based out of our Herndon, VA location with the option of a remote work schedule ... RF measurement experience and use of RF test and measurement Equipment such as Spectrum Analyzers ...

Babel Street

Software Engineer III

Reston, VA · On-site +1

$59.75 - $80.25/hr

... measures. Candidates near our Somerville, MA or Reston, VA offices are preferred but remote work it potential for the ideal candidate. ROLE FOCUS; As a Software Engineer III specializing in data ...

Atreides

Mission (Data) Engineer

Arlington, VA · Remote

$131K - $158K/yr

Embrace the 'measure twice, cut once' philosophy * Value and encourage diverse ideas and ... Flexible remote work environment * Additional benefits like flexible hours, work travel ...

U.S. Marine Corps

GENERAL ENGINEER

Quantico, VA · On-site +1

$102K - $158K/yr

... remote or isolated sites. You must be able to travel on military and commercial aircraft for ... Measurement, and Diagnostic Equipment) - Weapons/Sensors Development/Integration (i.e., MAGTF C2 ...

Booz Allen Hamilton, Inc.

Remote Work: No Job Number: R0240584 Location: King George,VA,US Share job via: Share Laser Weapon ... measuring system characteristics such as laser power and beam profiles for both fixed and mobile ...

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Remote Measurement Engineer information

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

To thrive as a Remote Measurement Engineer, you need a solid background in instrumentation, data analysis, and engineering principles, usually supported by a degree in engineering or a related field. Familiarity with remote sensing technologies, data acquisition systems, and software such as MATLAB or LabVIEW is commonly required. Strong problem-solving abilities, attention to detail, and effective communication skills help you excel in troubleshooting and collaborating with remote teams. These skills are crucial for ensuring accurate measurements, reliable data transmission, and successful project outcomes in distributed or off-site environments.

What is a remote measurement engineer?

Remote Measurement Engineers are professionals who specialize in designing, implementing, and maintaining systems that collect and analyze data from remote locations. They utilize various technologies such as sensors, data loggers, and communication networks to monitor and measure physical conditions or performance metrics from a distance. Their work is crucial in industries like oil and gas, environmental monitoring, and utilities, where on-site data collection may be difficult or hazardous. Remote Measurement Engineers ensure the accuracy and reliability of the collected data, enabling informed decision-making and efficient operations.

What is the difference between Remote Measurement Engineer vs Remote Data Analyst?

AspectRemote Measurement EngineerRemote Data Analyst
Required CredentialsBachelor's in Engineering, certifications in measurement toolsBachelor's in Statistics, certifications in data analysis
Work EnvironmentField measurements, technical software, remote collaborationData interpretation, reporting, remote analysis
Industry UsageManufacturing, engineering, infrastructureBusiness, finance, marketing

Remote Measurement Engineers focus on collecting and analyzing physical measurement data in technical fields, often working with engineering tools. Remote Data Analysts interpret data sets to inform business decisions. While both roles require analytical skills and remote work capabilities, their industry focus and technical expertise differ significantly.

How does a remote measurement engineer typically collaborate with on-site engineering teams and field technicians?

Remote Measurement Engineers often work closely with on-site teams to calibrate, troubleshoot, and maintain measurement systems from a distance. Collaboration usually happens via video conferences, remote desktop tools, and cloud-based data platforms, allowing engineers to provide real-time support and analysis. Regular communication is key, as remote engineers may need to interpret sensor data, guide field technicians through complex procedures, and ensure that measurement standards are met without being physically present. Building strong remote working relationships and maintaining clear documentation are essential to success in this role.
What are the most commonly searched types of Measurement Engineer jobs in Virginia? The most popular types of Measurement Engineer jobs in Virginia are:
What are popular job titles related to Remote Measurement Engineer jobs in Virginia? For Remote Measurement Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Remote Measurement Engineer jobs in Virginia look for? The top searched job categories for Remote Measurement Engineer jobs in Virginia are:
What cities in Virginia are hiring for Remote Measurement Engineer jobs? Cities in Virginia with the most Remote Measurement Engineer job openings:
Remote Measurement Engineer jobs near you
Infographic showing various Remote Measurement Engineer job openings in Virginia as of July 2026, with employment types broken down into 89% Full Time, 6% Part Time, and 5% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

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 7 days ago

Sentara Health rating

6.8

Company rating: 6.8 out of 10

Based on 398 frontline employees who took The Breakroom Quiz

492nd of 887 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!
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
• Reimbursement for certifications and free access to complete CEUs and professional development
• 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.

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