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- Tasks: Design advanced environmental engineering problems and evaluate AI-generated solutions.
- Company: Join Alignerr, a leader in AI research collaboration.
- Benefits: Earn $35–$60/hour with flexible remote work and freelance perks.
- Why this job: Make an impact on cutting-edge AI projects while enhancing your skills.
- Qualifications: Master’s or PhD in Environmental Engineering or related field required.
- Other info: Enjoy autonomy, flexibility, and potential for contract extension.
The predicted salary is between 28 - 48 ÂŁ 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.
Location: Remote
Organization: Alignerr | Type: Hourly Contract | Compensation: $35–$60 /hour | Commitment: 10–40 hours/week
What You’ll Do
- Develop Complex Problems: Design advanced environmental engineering problems across domains such as contaminant transport, mass balance in treatment plants, hydrology, and Life Cycle Assessments (LCA).
- Author Ground‑Truth Solutions: Create rigorous, step‑by‑step technical solutions, including chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations that serve as "golden responses."
- Technical Auditing: Evaluate AI‑generated remediation plans, environmental impact statements, and mathematical proofs for technical accuracy, safety, and adherence to regulatory standards (e.g., EPA, ISO 14001).
- Refine Reasoning: Identify logical fallacies in AI reasoning—such as incorrect stoichiometry in biological processes or failure to account for secondary environmental impacts—and provide structured feedback to improve the model’s "thinking" process.
Requirements
- Advanced Degree: Master’s (pursuing or completed) or PhD in Environmental Engineering, Civil Engineering (with an environmental focus), or a closely related field.
- Domain Expertise: Strong foundational knowledge in core areas such as aquatic chemistry, wastewater process design, air quality engineering, or hazardous waste remediation.
- Analytical Writing: Ability to communicate complex ecological and engineering concepts clearly and concisely in written form.
- Attention to Detail: High level of precision when checking unit conversions (e.g., mg/L to ppm), chemical equations, and regulatory compliance logic. No AI experience required.
Preferred
- Prior experience with data annotation, data quality, or evaluation systems.
- Familiarity with environmental modeling software.
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.
Environmental Engineering - AI Data Trainer employer: Alignerr
Contact Detail:
Alignerr Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Environmental Engineering - AI Data Trainer
✨Tip Number 1
Network like a pro! Reach out to professionals in the environmental engineering field on LinkedIn or at industry events. 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 projects, especially those related to contaminant transport or hydrology. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions in environmental engineering. Practice explaining complex concepts clearly, as communication is key in this role. We want to see how you think!
✨Tip Number 4
Don’t forget to apply through our website! It’s quick and easy, and we review applications daily. Completing your AI interview and application steps promptly can give you an edge in the hiring process.
We think you need these skills to ace Environmental Engineering - AI Data Trainer
Some tips for your application 🫡
Tailor Your Resume: Make sure your resume highlights your relevant experience in environmental engineering and any specific projects you've worked on. We want to see how your skills align with the role, so don’t be shy about showcasing your expertise!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about environmental engineering and how you can contribute to our AI projects. Keep it concise but engaging—let us know what makes you tick!
Showcase Your Analytical Writing Skills: Since strong writing is key for this role, include examples of your analytical writing in your application. Whether it's reports, research papers, or technical documents, we want to see how you communicate complex ideas clearly.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Alignerr
✨Know Your Stuff
Make sure you brush up on your environmental engineering knowledge, especially in areas like contaminant transport and hydrology. Be ready to discuss specific problems you've tackled in the past and how they relate to the role.
✨Showcase Your Writing Skills
Since analytical writing is key for this position, prepare to share examples of your written work. Whether it's a report or a technical paper, highlight how you clearly communicated complex concepts.
✨Attention to Detail is Key
During the interview, demonstrate your precision by discussing how you ensure accuracy in your work. Talk about your process for checking calculations and compliance with regulations—this will show you're detail-oriented.
✨Be Ready to Evaluate AI
Since you'll be auditing AI-generated plans, think about how you would approach this task. Prepare to discuss any experience you have with data quality or evaluation systems, even if it's not directly related to AI.
