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F1 Engineering Jobs in Virginia (NOW HIRING)

Socket.dev

AI Model Engineer

Ashburn, VA · On-site

$125 - $150/hr

Everforth ECS is seeking an AIModel Engineer to work in a hybrid remote/onsite capacity, with ... Strong understanding of model evaluation metrics (e.g., precision, recall, F1) and statistical ...

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F1 Engineering information

See Virginia salary details

$38.7K

$122.3K

$188.9K

How much do f1 engineering jobs pay per year?

As of Sep 5, 2026, the average yearly pay for f1 engineering in Virginia is $122,341.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,200.00 and $145,200.00 per year, depending on experience, location, and employer.

What is F1 engineering?

F1 engineering refers to the specialized field of designing, developing, and optimizing Formula 1 race cars. It involves a multidisciplinary team of engineers who focus on areas such as aerodynamics, materials science, mechanical systems, electronics, and data analysis to maximize the performance, safety, and reliability of F1 vehicles. F1 engineering is highly competitive and fast-paced, requiring innovative solutions and constant adaptation to evolving regulations and technologies. Professionals in this field work closely with drivers and teams to ensure the car's setup and strategy are optimized for each race. The role demands a deep understanding of physics, engineering principles, and teamwork.

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

To thrive as an F1 Engineer, you need a strong background in mechanical or automotive engineering, advanced mathematics, and physics, typically supported by a relevant engineering degree. Proficiency in CAD software, data analysis tools, and simulation systems like CFD and FEA is essential, along with familiarity with telemetry systems. Outstanding problem-solving, teamwork, and communication skills help you adapt quickly and collaborate effectively under intense pressure. These skills and qualities are critical for optimizing car performance, ensuring safety, and driving innovation in the fast-paced world of Formula 1.

What are some typical challenges faced by F1 engineers during a race weekend, and how do teams address them?

F1 engineers often face challenges such as rapidly changing weather conditions, unexpected technical issues, and the need to adapt car setups for optimal performance. Communication and flexibility are crucial, as engineers must collaborate closely with drivers, strategists, and mechanics to analyze real-time data and make quick decisions. Teams address these challenges through thorough preparation, simulation work, and leveraging advanced telemetry systems to monitor car performance and predict potential problems. This dynamic environment requires engineers to remain calm under pressure and think creatively to help the team succeed.

What is the difference between F1 Engineering vs Mechanical Engineering?

AspectF1 EngineeringMechanical Engineering
Required CredentialsDegree in engineering, specialized F1 racing certificationsBachelor's or Master's in Mechanical Engineering, professional licensure
Work EnvironmentHigh-pressure, fast-paced motorsport teams, on-track and lab settingsManufacturing, design, research labs, and various industries
Industry UsagePrimarily motorsport, automotive racing teamsBroad industry including automotive, aerospace, manufacturing

F1 Engineering focuses on high-performance racing car design and development within motorsport teams, requiring specialized certifications and working in dynamic, high-stakes environments. Mechanical Engineering offers a broader scope across multiple industries, emphasizing design, analysis, and manufacturing processes. While both fields share foundational engineering principles, F1 Engineering is highly specialized for racing applications, whereas Mechanical Engineering provides versatile career options.

Is it hard to get an engineering job in F1?

Getting an engineering job in F1 is highly competitive due to the industry's specialized skills, advanced technology, and limited openings. Candidates typically need a strong background in engineering, experience with simulation tools, and relevant internships or projects to improve their chances.

What are popular job titles related to F1 Engineering jobs in Virginia?

For F1 Engineering jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching F1 Engineering jobs in Virginia look for?

The top searched job categories for F1 Engineering jobs in Virginia are:

F1 Engineering jobs near you
Infographic showing various F1 Engineering job openings in Virginia as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $122,341 per year, or $58.8 per hour.

AI Model Engineer

Socket.dev

Ashburn, VA • On-site

$125 - $150/hr

Other

Posted yesterday

New

Job description

Everforth ECS is seeking an AIModel Engineerto work in a hybrid remote/onsite capacity, with minimum of 3 business days onsite at our Fairfax, VA corporate office and/or our Ashburn, VA customer site.

Please note: This position is contingent upon contract award

Everforth ECS is seeking an accomplishedAI/MLEngineerto provide technical leadership and strategic guidance on the integration of advanced artificial intelligence and machine learning solutions to support mission-critical government and defense objectives. The ideal candidate is innovative with a track record of evaluating, experimenting with, and transitioning emerging technologies into operational use. This role requires exceptional communication skills, strong technical expertise, and experience collaborating across the Department of Homeland Security (DHS) and other government agencies.TheAIEngineerwill design, train, implement, andmaintainend-to-end machine learning algorithms and their pipelines, automating deployment and monitoring processes while ensuring performance, observability, and security. This role contributes to building scalable infrastructure, real‑time dashboards, and automated pipelines that enable secure, compliant, and efficientAIoperations aligned with mission and business goals.

Key responsibilities include:

  • Design, build,train, and fine tunecomputer vision models for object detection, tracking, and classification tasks.
  • Utilize multimodal architectures for robust retrieval and data fusion.
  • Coordinate the planning, development, and execution of cutting-edge research programs designed to experimentally validate novelAI/ML concepts.
  • Evaluate emerging technologies from academia and industry for their potential impact on national security.
  • Serve as a subject matter expert, providing technical leadership and strategic recommendations to government decision-makers onAI/ML technology, adoption, and implementation.
  • Set the technical direction for advanced computer vision and AI capabilities supporting exploitation of remote sensing data, including EO and hyperspectral imagery.
  • Conduct rapid feasibility studies and prototype implementations to evaluate emerging algorithms, model architectures, and data exploitation approaches.
  • Use prototype-driven demonstrations and technical studies to shape applied research programs and support proposal development for new AI initiatives.
  • Advance the application of vision-language and multimodal foundation models for analysis, retrieval, and reasoning over large-scale EO/IR and hyperspectral datasets.
  • Work closely with mission partners to refine problem definitions, evaluate prototype systems, and ensure developed capabilities transition rapidly into operational environments.
  • Prepare and deliver high-quality technical briefings, documentation, and presentations for both technical and non-technical audiences
  • Utilizing data pipelines in Databricks, Apache Spark, and related ETL technologies (e.g., AWS Glue, ApacheAirflow).
  • Ensuring compliance with DHS security and accreditation standards, including STIGs and Impact Level controls.
  • Providing architectural oversight on data ingestion, curation, and storage to produce reliable, high-quality datasets forAI/ML development.
  • Supporting DevSecOps practices, CI/CD pipelines, and automation to streamline delivery.

Salary Range: $125,000-$150,000

General Description of Benefits

Qualifications
  • Must be a US Citizen with the ability to obtain and maintain a Public Trust determination
  • Minimum Bachelor’s degree in Computer Science, ElectricalEngineering, or a related technical field
  • 6+ years of experience in softwareengineering, dataengineering, and cloud architecture
  • Proficiency withAI/ML frameworks (e.g., TensorFlow, PyTorch, YOLO, ONNX)
  • Proficiency in Linux -- system administration, scripting in Bash, troubleshooting
  • Strong foundation inAI/ML algorithms and ability to implement agentic workflow, and promptengineering
  • Experienceinlarge language model (LLM) applications
  • Strong understanding of model evaluation metrics (e.g., precision, recall, F1) and statistical drift detection methods
  • Expertise in containerization and orchestration (Docker, Kubernetes, OpenShift) and CI/CD automation (GitHub Actions, Jenkins)
  • Proficiency in building and managing ETL pipelines (e.g. AWS Glue, ApacheAirflow)
  • Strong communication skills with the ability to interface and collaborate with project managers, stakeholders, vendors, and technical staff
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