Senior Machine Learning Engineer

Alignerr; España; Remote; EUR 74,000 - 135,000; Part time

Job summary

Alignerr is seeking a Senior Machine Learning Engineer (AI Training) for a fully remote hourly contract. You will craft high‑fidelity reasoning traces that teach how AI should plan, reason, and decide across complex real‑world tasks.

The role is fully remote with 10–40 hours per week and collaboration with a global ML team. The candidate is an experienced ML engineer, capable of breaking down ambiguous problems into structured reasoning, with deep knowledge of LLMs, their training dynamics, and

Qualifications

• Experienced ML engineer with focus on model reasoning, training, or evaluation.
• Ability to break down complex problems into structured steps.
• Deep familiarity with how LLMs work, including failure modes and training dynamics.
• Clear, precise written communicator who can articulate complex reasoning.
• Self-directed and productive in asynchronous environments.

Responsibilities

• Author high-fidelity reasoning traces showing how AI should plan, use tools, and decide across complex tasks.
• Decompose complex problems into clear, logical, well-documented steps for model training ground truth.
• Review and mentor quality of structured traces for accuracy and consistency.
• Design data strategies to help LLMs navigate multi-step decisions.
• Collaborate with a global team of ML researchers on frontier AI projects.

Skills

ML Engineering

LLMs

AI Training

Model Reasoning

Data Annotation

Job description

Senior Machine Learning Engineer (AI Training)

About The Role

What if your deep expertise in machine learning could directly shape how AI reasons, plans, and solves complex problems for millions of people? We're looking for Senior Machine Learning Engineers to author high-fidelity reasoning traces that teach cutting-edge LLMs how to think — step by step, decision by decision.

This is a fully remote, flexible contract role built for experienced ML professionals who understand model behavior at a deep level and can translate that understanding into structured, actionable training data.

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

What You'll Do

• Author complex, high-fidelity reasoning traces that capture how an AI should plan, use tools, and make decisions across sophisticated real-world tasks
• Decompose difficult technical problems into clear, logical, well-documented steps that serve as ground truth for model training
• Review and mentor the quality of structured traces produced by others, ensuring accuracy, consistency, and optimal planning documentation
• Design data strategies that help LLMs navigate intricate, multi-step decision-making scenarios
• Collaborate with a global team of ML professionals working at the frontier of AI research

Who You Are

• Experienced machine learning engineer or researcher with a strong foundation in model reasoning, training, or evaluation
• Able to break down complex, ambiguous problems into structured, logical reasoning chains
• Deeply familiar with how LLMs work — including their failure modes, capabilities, and training dynamics
• Detail-oriented and rigorous in your thinking — you care about getting things exactly right
• A clear, precise written communicator who can articulate complex reasoning accessibly
• Self-directed and productive when working independently in an async environment

Nice to Have

• Prior experience with data annotation, data quality workflows, or model evaluation systems
• Familiarity with RLHF, chain-of-thought prompting, or related alignment techniques
• Top-tier Kaggle competition results (Grandmaster or Master level) demonstrating elite model performance and feature engineering skills
• Background in AI safety, interpretability, or responsible AI development

Why Join Us

• Work at the frontier — your contributions directly influence how next-generation AI models reason and behave
• Fully remote and flexible — work when and where it suits you, on your own schedule
• Freelance autonomy with the structure and purpose of meaningful, high-impact technical work
• Collaborate with world-class ML researchers and AI labs on projects that matter
• Potential for ongoing work and contract extension as new projects launch