Senior Machine Learning Engineer
Alignerr • Remote • Posted 0 days ago
Education
Any
Type
Pay Rate
$70/task
Posted
0d ago
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About this Role
Senior Machine Learning Engineer - AI Data Trainer
- Location: Remote
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. This project is about capturing how an LLM reasons and takes actions step by step to solve real tasks. Annotators write clear, structured traces that show planning, tool use, and decision making, creating data that trains models to reason more reliably in real world scenarios. Organization: Alignerr Position: Senior Machine Learning Engineer - AI Data Trainer Type: Hourly Contract Compensation: $60–$80 /hour Location: Remote Commitment: 10–40 hours/week
What You’ll Do:
- Lead the authorship of complex, high-fidelity reasoning traces for sophisticated technical tasks.
- Mentor and review structured traces to ensure optimal planning and tool-use documentation.
- Design data strategies that help LLMs navigate intricate real-world decision-making scenarios.
Requirements:
Preferred:
- Significant experience in Machine Learning or related technical fields, with a focus on model reasoning.
- Proven ability to decompose complex problems into clear, logical, and documented steps.
- Experience with advanced LLM evaluation and training methodologies.
- Prior experience with data annotation, data quality, or evaluation systems.
- Top-tier Kaggle competition results (e.g., Grandmaster/Master level), demonstrating a deep understanding of model performance and feature engineering.
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)
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
- Submit your resume
- Complete a short screening
- Project matching and onboarding
Requirements
- Significant experience in Machine Learning or related technical fields, with a focus on model reasoning.
- Proven ability to decompose complex problems into clear, logical, and documented steps.
- Experience with advanced LLM evaluation and training methodologies.
- Prior experience with data annotation, data quality, or evaluation systems.
- Top-tier Kaggle competition results (e.g., Grandmaster/Master level), demonstrating a deep understanding of model performance and feature engineering.
Compensation Analysis
At Alignerr, we partner with the world’s leading AI research teams and labs to build and train cutting-edge AI models. This project is about capturing how an LLM reasons and takes actions step by step to solve real tasks. Annotators write clear, structured traces that show planning, tool use, and decision making, creating data that trains models to
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Frequently Asked Questions
What is the assessment actually like?
Notoriously strict. Alignerr uses TestGorilla for role-specific timed tests — a blank coding environment for engineers, rigorous grammar and fact-checking for writers. There is almost no hand-holding. The critical catch: this is essentially a one-shot process. Fail or abandon the assessment, and you are typically locked out of that role permanently with no option to retake.
How quickly can I start earning after I pass?
Not immediately. Even after passing the assessment and completing identity verification (via Persona) and billing setup (via Deel), you may sit in a waiting pool for weeks or months. You only start earning when a project matching your specific skills launches and you are officially assigned. Do not plan around Alignerr income until you are actively on a project.
Is there a community?
Yes — and it is one of Alignerr's genuine strengths. Once assigned to a project, you are added to Slack channels where you can ask questions, get rubric clarifications from admins, and talk to other AI trainers. This is rare in AI training and makes a real difference when guidelines are ambiguous or change mid-project.
What does the work actually look like?
It is practical, hands-on data work. You might be recording short videos, categorizing images, rating text responses, or analyzing data. The tasks are designed to be short and distinct—typically 5-60 minutes per task.
How flexible is the schedule?
Extremely. This is true "log in and work" flexibility. You can usually work for 20 minutes or 4 hours depending on your availability. There are rarely minimum hour requirements, making it ideal for side income.
Is there an interview?
Usually, no. Hiring for these roles is almost entirely based on passing an automated assessment or "qualification" task. If you pass the test, you get access to the work.
What is the barrier to entry?
Alignerr is known for difficult technical assessments. You must pass a timed test in your specific domain (e.g., Python, Physics, or Language) before you are eligible for any paid projects.