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F1 Engineer Jobs in Virginia (NOW HIRING)

Senior AI Engineer

Falls Church, VA ยท On-site

$111K - $153K/yr

... recall, F1 scores, latency thresholds, and throughput benchmarks to validate operational ... engineers, cybersecurity teams, and mission leads to integrate AI enhancements into enterprise ...

Junior AI/ML Engineer Location: Herndon, VA (Hybrid Work) Preferred: US Citizenship Node.Digital is ... recall, F1 score, AUC-ROC, confusion matrices) for government review in EPLC-required model ...

Software Engineer

Arlington, VA ยท On-site

$90K - $110K/yr

Your Career We're looking for a talented early-career Software Engineer and collaborative problem ... provide F1-OPT or other visa sponsorship. Our Commitment We're trailblazers who dream big, take ...

We are looking for a skilled test engineer to join our team focused on testing the O-RAN DU ... In-depth knowledge of O-RAN architecture and interfaces (F1, E2, Open Fronthaul, A1, etc.

We are looking for a skilled test engineer to join our team focused on testing the O-RAN DU ... In-depth knowledge of O-RAN architecture and interfaces (F1, E2, Open Fronthaul, A1, etc.

The role partners across the business unit, data engineering, and AI teams to ensure the platform ... F1 STEM OPT, F1 CPT, etc.) now or in the future. If you will require McKesson to provide ...

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Showing results 1-20

F1 Engineer information

See Virginia salary details

$30.7K

$95K

$126.4K

How much do f1 engineer jobs pay per year?

As of Jun 28, 2026, the average yearly pay for f1 engineer in Virginia is $94,974.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,300.00 and $115,000.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior engineers in specialized fields such as aerospace, petroleum, or software engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and leadership roles. High compensation often includes bonuses, stock options, or profit sharing, particularly in large corporations or high-demand industries.

What are F1 Engineers?

F1 Engineers are specialized professionals who design, develop, and optimize the performance of Formula 1 cars. They work in various roles such as race engineers, performance engineers, and design engineers, collaborating closely with drivers and technical teams. Their responsibilities include analyzing data, improving car setups, and ensuring compliance with regulations to achieve maximum speed and reliability on the track. F1 Engineers play a crucial role in a team's success during both races and development phases.

How much do F1 engineers get paid?

F1 engineers typically earn between $50,000 and $150,000 annually, depending on experience, team size, and location. Senior engineers or those working for top teams can earn higher salaries, often exceeding $200,000 with bonuses and benefits included.

Is 21 too old to start F1?

F1 engineers typically start their careers in engineering or related fields and can enter the industry at various ages. While most professionals begin in their early 20s or later, age is less important than relevant skills, experience, and education such as a degree in mechanical, electrical, or automotive engineering. Starting at 21 is generally not too late to pursue a career as an F1 engineer if you have the necessary qualifications and technical knowledge.

What are the key skills and qualifications needed to thrive as a F1 Engineer, and why are they important?

To thrive as a F1 Engineer, you need a deep understanding of mechanical or automotive engineering, advanced problem-solving abilities, and typically a relevant engineering degree. Familiarity with CAD software, telemetry systems, and simulation tools, as well as experience with rapid prototyping and data analysis platforms, is crucial. Excellent teamwork, communication, and the ability to perform under pressure distinguish top candidates in this high-stakes environment. These skills and qualities are vital to ensuring innovation, precision, and seamless collaboration in the fast-paced world of Formula 1 racing.

Does F1 hire engineers?

F1 teams regularly hire engineers for roles such as aerodynamics, vehicle design, data analysis, and systems engineering. Candidates typically need a strong background in engineering, experience with simulation tools, and knowledge of motorsport or automotive technology.

What is the difference between F1 Engineer vs Race Engineer?

AspectF1 EngineerRace Engineer
CredentialsEngineering degree, motorsport certificationsEngineering degree, motorsport certifications
Work EnvironmentF1 teams, race tracks, engineering labsF1 teams, race tracks, engineering labs
Industry UsageDesign, development, testing of F1 carsCommunication, strategy, car setup during races
Primary FocusTechnical development and analysisReal-time race strategy and driver communication

While both F1 Engineers and Race Engineers work within the motorsport industry, F1 Engineers focus on the technical development and testing of the car, whereas Race Engineers handle real-time race strategy and driver communication during events. Both roles require engineering expertise and are integral to a team's success in Formula 1 racing.

What are some common challenges F1 Engineers face when working with race teams during a season?

F1 Engineers often encounter the challenge of adapting quickly to changing race conditions and regulations, which requires constant problem-solving and innovative thinking. They work in high-pressure environments where split-second decisions can impact race outcomes, and collaboration with drivers, mechanics, and other engineers is crucial. Additionally, balancing the need for performance improvements with strict technical regulations and tight deadlines can be demanding. These challenges make the role dynamic and rewarding for those who thrive in fast-paced, team-oriented settings.
What cities in Virginia are hiring for F1 Engineer jobs? Cities in Virginia with the most F1 Engineer job openings:
Infographic showing various F1 Engineer job openings in Virginia as of June 2026, with employment types broken down into 81% Full Time, and 19% Contract. Highlights an 81% In-person, and 19% Remote job distribution, with an average salary of $94,974 per year, or $45.7 per hour.
Senior AI Engineer

Senior AI Engineer

ECS

Falls Church, VA โ€ข On-site

$111K - $153K/yr

Full-time

Posted 8 days ago


Job description

Everforth ECS is seeking a Senior AI Engineer to work in the National Capital Region covering the Pentagon, Falls Church, and Fairfax. Please Note: This position is contingent upon contract award.
The War Data Platform (WDP) is a key initiative within the U.S. Department of War's (DoW) AI-First strategy introduced in early 2026. The WDP separates business and financial data from operational warfighting data, aiming to accelerate the deployment of artificial intelligence (AI) on the battlefield. The WDP extends to Unclassified, Secret, and Top Secret environments, and supports collaboration between Combatant Commands, Joint Staff directorates, Senior Executive Service leaders, and operational analysts.
The Senior AI Engineer serves as a senior-level AI architect and practitioner responsible for designing, building, and deploying advanced artificial intelligence capabilities that modernize WDP Core Integration's operational support functions across all classification tiers. This role leverages machine learning, natural language processing, and retrieval-augmented generation techniques to automate mission-critical workflows, accelerate request resolution, and strengthen WDP's AI-enabled user experience from the Pentagon to the tactical edge.
โ€ข Designs and implements advanced artificial intelligence capabilities supporting War Data Platform (WDP) Core Integration modernization objectives by developing automated mechanisms that accelerate request intake, categorization, triage, and routing across Tier 0 through Tier 3 support channels for customers across NIPRNet, SIPRNet, and JWICS enclaves.
โ€ข Builds and deploys machine learning classification pipelines, natural language processing models, and retrieval-augmented generation components using platforms such as Python, PyTorch, TensorFlow, SageMaker, Amazon Comprehend, and Elasticsearch to identify intent, assign routing paths, and detect anomalous patterns within high-volume operational data streams.
โ€ข Integrates AI-driven chatbots, recommender engines, and knowledge discovery modules into the WDP Core Integration user experience to provide instant guidance, dynamic knowledge article suggestions, and automated resolution workflows aligned to Government-approved Standard Operating Procedures and mission readiness objectives.
โ€ข Conducts model evaluation using precision, recall, F1 scores, latency thresholds, and throughput benchmarks to validate operational suitability for Combatant Command, Service Headquarters, Joint Staff, and Senior Executive Service mission users.
โ€ข Produces deliverables including automation roadmaps, machine learning architecture diagrams, system interface specifications, AI-enabled workflow designs, performance dashboards, and modernization impact reports.
โ€ข Collaborates with platform engineers, cybersecurity teams, and mission leads to integrate AI enhancements into enterprise pipelines while reducing ticket resolution times, eliminating bottlenecks, and driving continuous improvement in user sentiment metrics, SLA compliance, and cross-enclave operational efficiency.
โ€ข Performs other duties as assigned.
โ€ข Current Secret security clearance with the ability to obtain and maintain a Top Secret (TS) security clearance.
โ€ข A minimum of 10 years of experience in artificial intelligence engineering, machine learning development, or a closely related discipline within a federal, defense, or enterprise technology environment, with demonstrated senior-level expertise designing and deploying production-grade AI/ML systems at scale.
โ€ข Hands-on proficiency developing and operationalizing machine learning classification pipelines, natural language processing models, and retrieval-augmented generation architectures using Python and one or more of the following frameworks and platforms: PyTorch, TensorFlow, SageMaker, Amazon Comprehend, or Elasticsearch, including experience deploying these capabilities into multi-enclave government or cloud environments.
โ€ข Demonstrated experience integrating AI-driven automation - including chatbots, recommender systems, and automated triage workflows - into enterprise operational support or data platform environments, with the ability to validate model performance using standard evaluation metrics such as precision, recall, F1 score, and latency benchmarks in support of production readiness requirements.
โ€ข Experience producing formal AI engineering deliverables including automation roadmaps, ML architecture diagrams, system interface specifications, and performance dashboards, with the ability to effectively communicate technical AI concepts and design decisions to program managers, platform engineers, cybersecurity teams, and senior government stakeholders.
โ€ข Strong problem-solving and decision-making capabilities, with a proven ability to weigh the relative costs and benefits of potential actions and identify the most appropriate solution.
โ€ข Highly developed interpersonal and oral/written communication skills, with the ability to effectively and professionally interact with a diverse set of stakeholders (from peers to end-users to executive management).