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Our formula is simple: hire the best people, find out what they enjoy and are great at, and help ... substituted for one year of experience). * Excellent written & verbal communication skills.
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Formula 1 Engineer information
See Raleigh, NC salary details
$12.62 - $18.61
2% of jobs
$18.61 - $24.60
6% of jobs
$24.60 - $30.59
10% of jobs
$30.59 - $36.58
6% of jobs
$37.58 is the 25th percentile. Wages below this are outliers.
$36.58 - $42.57
3% of jobs
$42.57 - $48.56
6% of jobs
$48.56 - $54.55
9% of jobs
The median wage is $58.36 / hr.
$54.55 - $60.54
12% of jobs
$60.54 - $66.53
12% of jobs
$70.45 is the 75th percentile. Wages above this are outliers.
$66.53 - $72.52
14% of jobs
$72.52 - $78.51
20% of jobs
$12
$54
$78
How much do formula 1 engineer jobs pay per hour?
What is the difference between Formula 1 Engineer vs Motorsport Engineer?
| Aspect | Formula 1 Engineer | Motorsport Engineer |
|---|---|---|
| Required Credentials | Engineering degree, specialized motorsport knowledge | Engineering degree, motorsport experience |
| Work Environment | F1 teams, high-pressure, high-tech labs | Various motorsport teams, racetracks, workshops |
| Industry Usage | Primarily Formula 1 racing | Various motorsport disciplines (e.g., rally, endurance) |
Formula 1 Engineers and Motorsport Engineers both require engineering degrees and motorsport experience. F1 Engineers focus specifically on Formula 1 teams, working in high-pressure environments with cutting-edge technology. Motorsport Engineers may work across different racing disciplines, including rally or endurance racing, often in diverse settings. While their skills overlap, F1 Engineers specialize in the unique demands of Formula 1 racing.
How do you get a job as an engineer in F1?
What are the main collaborative challenges Formula 1 Engineers face during a race weekend?
What are the key skills and qualifications needed to thrive as a Formula 1 Engineer, and why are they important?
How much do F1 engineers get paid?
What are Formula 1 Engineers?
What engineering jobs are in F1?
How much do Red Bull F1 engineers get paid?

Other
Medical, Life, Retirement, PTO
Posted 17 days ago
Key responsibilities
Own and drive end-to-end system test strategy, defining coverage aligned to customer workflows and risk areas.
Design and implement scalable regression frameworks with parallel execution and smart test selection.
Mentor engineers on AI-driven testing strategies and modern QA practices.
Job description
NetApp is pioneering the development of StorageGRID object storage - AWS cloud compatible software powering the exponential growth in AI data lakes. As a Software Developer Engineer in Test, this is your chance to work alongside a group of talented developers, impart your vision, and rapidly launch the latest cloud storage software. Your incredible testing and automation skills will create opportunities to contribute clean code. Naturally, you are as comfortable solving our customer's AI data lake challenges by writing new code as you are improving productivity by refactoring. You are opinionated while flexible and know when to adopt new technologies.ย
We are true believers of Agile development and have been on the journey for many years. Since you maintain supreme levels of communication with your peers, we won't inundate you with process and documentation as you work in our flexible hybrid work-from-home/office model.ย
Throughout the world, leading organizations count on NetApp to manage and store their data. From the edge of human endurance in Formula One auto racing to the edge of the universe with CERN's Large Hadron Collider, we help our customers do things they couldn't before-at speeds you never thought possible.ย
Role Overviewย
In this role, you will serve as a key technical leader and force multiplier for our established, high-performing Software Quality team. Your deep passion for software quality will drive meaningful improvements: introducing effective processes, tools, and technologies; mentoring engineers to strengthen their test design and automation skills; and guiding the team's progression from primarily functional testing to addressing sophisticated challenges such as race conditions, scalability, stability, and performance in distributed systems.
- Own and drive end-to-end system test strategy, defining coverage aligned to customer workflows and risk areas.ย
- Design and implement scalable regression frameworks with parallel execution and smart test selection.ย
- Leverage AI/GenAI for test case generation, including boundary, edge, and failure scenarios.ย
- Build AI-assisted and self-healing automation frameworks to reduce maintenance and improve resilience.ย
- Apply LLMs for test design, validation, debugging, and defect analysis.ย
- Use AI techniques for anomaly detection, log analysis, and failure triaging.ย
- Enable AI-driven synthetic test data generation for complex distributed workflows.ย
- Drive root-cause analysis using AI-assisted insights and data-driven debugging approaches.ย
- Integrate AI into CI/CD pipelines to improve feedback cycles and regression efficiency.ย
- Mentor engineers on AI-driven testing strategies and modern QA practices.ย
- Proven experience in system-level testing and automation frameworks.ย
- Strong technical foundation in distributed systems, cloud APIs, and Linux environments.ย
- Expertise in scripting languages such as Python or Ruby.ย
- Hands-on experience applying AI/ML techniques to software testing workflows.ย
- Experience with LLM-based tools for test generation, debugging, and validation.ย
- Ability to design AI-driven quality engineering solutions and frameworks.ย
- Familiarity with Agile development, CI/CD, and Test-Driven Development (TDD).ย
- Preferred Skillsย
- Experience testing large-scale distributed storage systems or complex enterprise platforms.ย
- Hands-on experience with AI-assisted testing, including test case generation and automation.ย
- Experience with prompt engineering for structured and reproducible test generation.ย
- Understanding of AI-specific failure patterns such as hallucinations and non-deterministic outputs.ย
- Ability to design guardrails and validation layers for AI-generated outputs.ย
- Experience with intelligent test prioritization and selection using ML techniques.ย
- Familiarity with agentic workflows and autonomous testing systems.ย
- Experience integrating AI into CI/CD pipelines for automated validation.ย
- Knowledge of synthetic data generation and data engineering for testing systems.ย
- Education & Experienceย
- A minimum of 10 years of experience is required. A Bachelor's or Master's degree in Computer Science, Engineering, or equivalent experience.ย
Compensation:
The target salary range for this position is 170,000 - 253,000 USD. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. The range is based on 'On Target Earnings' (OTE) representing the total potential earnings, which is the sum of the base salary and potential commission earned when performance targets are achieved. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, employee stock purchase plan, and/or restricted stocks (RSU's). These offerings are subject to regional variations and governed by local laws, regulations, and company policies. We will provide detailed information about the specific benefits for your region during the recruitment process.