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- Tasks: Design and develop complex mechanical engineering problems to test AI performance.
- Company: Join Alignerr, a leader in AI research collaboration.
- Benefits: Earn $35–$60/hour with flexible remote work options.
- Why this job: Work on cutting-edge AI projects and refine advanced language models.
- Qualifications: Masters or PhD in Mechanical Engineering or related field required.
- Other info: Enjoy freelance perks like autonomy and global collaboration.
The predicted salary is between 26 - 43 £ per hour.
About The Job
At Alignerr, we partner with the world’s leading AI research teams and labs to build and train cutting-edge AI models. You’ll challenge advanced language models on topics such as fluid dynamics, thermodynamics, structural mechanics, and mechatronics—documenting every failure mode so we can harden model reasoning.
Organization: Alignerr | Type: Hourly Contract | Compensation: $35–$60 /hour | Location: Remote | Commitment: 10–40 hours/week
What You’ll Do:
- Develop Complex Problems: Design advanced mechanical engineering problems across domains such as FEA (Finite Element Analysis), heat transfer, kinematics, and material science to test AI performance.
- Author Ground-Truth Solutions: Create rigorous, step-by-step technical solutions and "golden responses" that the AI will use as a benchmark for learning.
- Technical Auditing: Evaluate AI-generated CAD logic, thermodynamic proofs, and material specifications for technical accuracy, safety, and adherence to engineering standards (e.g., ASME, ISO).
- Refine Reasoning: Identify logical fallacies in AI reasoning—such as incorrect force distributions or energy conservation violations—and provide structured feedback to improve the model's "thinking" process.
Requirements:
- Advanced Degree: Masters (pursuing or completed) or PhD in Mechanical Engineering, Aerospace Engineering, or a closely related field.
- Domain Expertise: Strong foundational knowledge in core areas such as solid mechanics, fluid mechanics, CAD/CAM, or manufacturing processes.
- Analytical Writing: Ability to communicate highly technical concepts and complex physical phenomena clearly and concisely in written form.
- Attention to Detail: High level of precision when checking mathematical derivations, unit conversions, and physical system constraints. No AI experience required.
Preferred:
- Prior experience with data annotation, data quality, or evaluation systems.
- Proficiency in engineering software concepts (e.g., SolidWorks, MATLAB, ANSYS) to evaluate AI-generated code or workflows.
Why Join Us:
- Competitive pay and flexible remote work.
- Collaborate with a team working on cutting-edge AI projects.
- Exposure to advanced LLMs and how they’re trained.
- Freelance perks: autonomy, flexibility, and global collaboration.
- Potential for contract extension.
Application Process (Takes 15‑20 min):
- Submit your resume.
- Complete a short screening.
- Project matching and onboarding.
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
Mechanical Engineering - AI Data Trainer in Manchester employer: Alignerr
Contact Detail:
Alignerr Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Mechanical Engineering - AI Data Trainer in Manchester
✨Tip Number 1
Get your networking game on! Reach out to professionals in the mechanical engineering field, especially those involved with AI. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work in fluid dynamics, thermodynamics, or any relevant projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Don’t just apply—engage! When you submit your application through our website, follow up with a quick email expressing your enthusiasm for the role. It shows initiative and keeps you on their radar.
✨Tip Number 4
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss how you would tackle complex engineering problems, as this is key for the AI Data Trainer role.
We think you need these skills to ace Mechanical Engineering - AI Data Trainer in Manchester
Some tips for your application 🫡
Craft a Tailored Resume: Make sure your resume highlights your advanced degree and relevant experience in mechanical engineering. We want to see how your skills align with the job description, so don’t be shy about showcasing your expertise in areas like fluid dynamics or CAD.
Show Off Your Writing Skills: Since analytical writing is key for this role, include examples of your technical writing in your application. We’re looking for clarity and precision, so make sure your explanations are easy to follow and demonstrate your ability to communicate complex concepts.
Be Detail-Oriented: Pay close attention to the details in your application. Double-check for any typos or errors, especially in mathematical derivations or technical terms. We appreciate candidates who take the time to ensure their submissions are polished and professional.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It’s quick and easy, and it helps us keep track of your application. Plus, we review applications daily, so you won’t have to wait long to hear back from us!
How to prepare for a job interview at Alignerr
✨Know Your Stuff
Make sure you brush up on your mechanical engineering fundamentals, especially in areas like fluid dynamics and thermodynamics. Be ready to discuss specific problems you've solved or concepts you've mastered, as this will show your expertise and confidence.
✨Showcase Your Writing Skills
Since you'll need to communicate complex ideas clearly, prepare to demonstrate your analytical writing skills. Bring examples of technical documents or reports you've authored, and be ready to explain how you approach breaking down complicated topics.
✨Prepare for Technical Questions
Expect to face questions that test your understanding of CAD logic and material specifications. Practise explaining your thought process when solving engineering problems, and think about how you would critique AI-generated solutions.
✨Highlight Attention to Detail
Attention to detail is crucial in this role. Be prepared to discuss how you ensure accuracy in your work, whether it's through checking mathematical derivations or adhering to engineering standards. Share specific examples where your precision made a difference.
