Senior Machine Learning Expert

Alignerr Corp.; España; Remote; EUR 83,000 - 165,000; Full time

Job summary

Alignerr is seeking a Senior Machine Learning Expert to author reasoning traces that teach LLMs how to plan, reason, and solve problems. This is a remote, flexible hourly contract designed for experienced ML practitioners who understand model decision processes.

You will decompose complex problems into structured steps, design data strategies for multi-step reasoning, and ensure traces align with best practices in model training.

Qualifications

• Experienced in machine learning, AI research, or a closely related technical field — you understand how models reason and where they fail.
• Skilled at decomposing hard problems into clear, documented, logical steps.
• Familiar with LLM evaluation methodologies, training pipelines, or RLHF-style workflows.

Responsibilities

• Author complex, high-fidelity reasoning traces that document how an LLM should plan, use tools, and make decisions across sophisticated technical tasks
• Break down intricate real-world problems into clear, structured, logical steps that models can learn from
• Design and contribute to data strategies that help LLMs navigate multi-step decision-making scenarios reliably
• Review and refine reasoning traces for quality, completeness, and alignment with best practices in model training

Skills

Machine learning

AI research

Problem decomposition

Documentation

RLHF workflows

PyTorch

TensorFlow

Tools

PyTorch

TensorFlow

Kaggle

Job description

Senior Machine Learning Expert (AI Training)

What if your deep expertise in machine learning could directly shape how the world's most advanced AI systems think, plan, and solve problems? We're looking for Senior Machine Learning Experts to author the reasoning traces that teach LLMs how to reason step by step — turning your technical intuition into the training data that powers next-generation AI.

About The Role

This is a fully remote, flexible contract role designed for experienced ML practitioners who understand how models make decisions and want to influence that process from the inside.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 10–40 hours/week

What You'll Do

• Author complex, high-fidelity reasoning traces that document how an LLM should plan, use tools, and make decisions across sophisticated technical tasks
• Break down intricate real-world problems into clear, structured, logical steps that models can learn from
• Design and contribute to data strategies that help LLMs navigate multi-step decision-making scenarios reliably
• Review and refine reasoning traces for quality, completeness, and alignment with best practices in model training
• Apply your architectural and systems-level ML knowledge to ensure traces reflect how expert practitioners actually think

Who You Are

• Experienced in machine learning, AI research, or a closely related technical field — you understand how models reason and where they fail
• Skilled at decomposing hard problems into clear, documented, logical steps
• Familiar with LLM evaluation methodologies, training pipelines, or RLHF-style workflows
• Detail-oriented and rigorous — you care about getting things exactly right
• Comfortable working independently and asynchronously in a remote environment

Nice to Have

• Prior experience in data annotation, data quality, or AI evaluation systems
• Top-tier Kaggle competition results (Grandmaster or Master level), demonstrating elite-level understanding of model performance and feature engineering
• Background in NLP, reasoning systems, or agent-based model development
• Experience writing technical documentation or structured problem-solving guides

Why Join Us

• Work on some of the most technically challenging AI problems in the industry alongside leading research labs
• Fully remote and flexible — work when and where it suits you
• Freelance autonomy with the structure and purpose of meaningful, high-impact work
• Gain deep, hands-on exposure to how frontier LLMs are trained and evaluated
• Potential for ongoing work and contract extension as new projects launch