Senior Machine Learning Engineer

Alignerr; Delhi; Remote; INR 2,066,000 - 3,444,000; Full time

Job summary

Alignerr is seeking a Senior Machine Learning Engineer (AI Training) for a fully remote hourly contract. You will author complex reasoning traces and shape how models reason, plan, and solve problems at senior levels.

The role emphasizes structured documentation, evaluation, and data strategies to improve multi-step reasoning in state-of-the-art AI systems.

Qualifications

• Experience in ML/AI research and model behavior.
• Ability to decompose problems into clear steps.
• Knowledge of LLM training pipelines and evaluation.
• Precise, structured written documentation.

Responsibilities

• Author high-fidelity reasoning traces for complex tasks.
• Design and document structured traces showing reasoning.
• Review traces for clarity and technical accuracy.
• Develop data strategies enabling reliable, consistent reasoning.
• Apply architectural insight to reflect best practices in model decision-making.

Skills

ML engineering

Structured thinking

Documentation writing

LLM training pipelines

Job description

Senior Machine Learning Engineer (AI Training)

About The Role

What if your deep expertise in machine learning could directly influence how the next generation of AI systems reason, plan, and solve problems? We're looking for Senior Machine Learning Engineers to author high-fidelity reasoning traces — the structured, step-by-step thought processes that teach large language models how to think.

This is a fully remote, flexible contract role built for senior-level ML professionals who understand model behavior from the inside out. Your work won't just describe what AI does — it will shape how AI reasons.

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

What You’ll Do

• Author complex, high-fidelity reasoning traces that capture planning, tool use, and multi-step decision-making for sophisticated technical tasks
• Design and document structured traces that demonstrate how a model should reason through real-world scenarios — not just what the answer is, but how to get there
• Review and quality-check traces produced by other contributors, ensuring clarity, logical soundness, and technical accuracy
• Develop data strategies that help LLMs navigate ambiguous, multi-layered problems with reliable, consistent reasoning
• Apply senior-level architectural insight to ensure traces reflect best practices in model decision-making and problem decomposition

Who You Are

• Experienced in machine learning, AI research, or a closely related technical field — you understand how models learn and where they fail
• Skilled at decomposing complex problems into clear, documented, logical steps that others can follow and evaluate
• Familiar with LLM training pipelines, evaluation methodologies, and the mechanics of how models develop reasoning capabilities
• A precise, structured thinker who can translate expertise into high-quality written documentation
• Self-directed and reliable — you produce consistent, high-quality work without hand-holding

Nice to Have

• Prior experience with data annotation, data quality assurance, or AI evaluation systems
• Top-tier Kaggle competition results (Grandmaster or Master level) demonstrating elite-level model understanding and performance optimization
• Background in reinforcement learning, chain-of-thought prompting, or agentic AI systems
• Experience working with or evaluating frontier LLMs

Why Join Us

• Work directly with some of the world’s leading AI research teams and labs on cutting-edge model development
• Fully remote and flexible — structure your work around your life, not the other way around
• Freelance autonomy with meaningful, intellectually stimulating work on problems that actually matter
• Gain deep, hands-on exposure to how frontier LLMs are trained and evaluated
• Potential for ongoing work and contract extension as new projects launch