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alignerr
Senior Machine Learning Engineer - AI
alignerr
New Delhi•Remote•3-5 Yrs•1 hour ago
Job description
Remote
Overview
As a Senior Machine Learning Engineer specializing in AI Training, your role will involve authoring high-fidelity reasoning traces to teach large language models how to think.
Responsibilities
- Author complex reasoning traces that capture planning, tool use, and multi-step decision-making for sophisticated technical tasks.
- Review and quality-check traces produced by other contributors to ensure clarity, logical soundness, and technical accuracy.
- Develop data strategies to enable large language models to navigate ambiguous, multi-layered problems with reliable reasoning.
- Bring expertise in machine learning, AI research, or a closely related technical field to understand how models learn and identify areas where they may fall short.
- Be familiar with LLM training pipelines, evaluation methodologies, and the mechanics of how models develop reasoning capabilities.
- Demonstrate precise, structured thinking skills to effectively translate expertise into high-quality written documentation.
- Exhibit self-directed and reliable work ethic by consistently delivering high-quality work without constant supervision.
- Utilize prior experience in data annotation, data quality assurance, or AI evaluation systems to enhance project outcomes.
- Showcase top-tier Kaggle competition results at Grandmaster or Master level to demonstrate elite-level model understanding and performance optimization.
- Have a background in reinforcement learning, chain-of-thought prompting, or agentic AI systems.
- Engage in working with or evaluating frontier LLMs to contribute to cutting-edge model development.
- Author complex reasoning traces that capture planning, tool use, and multi-step decision-making for sophisticated technical tasks.
- Review and quality-check traces produced by other contributors to ensure clarity, logical soundness, and technical accuracy.
- Develop data strategies to enable large language models to navigate ambiguous, multi-layered problems with reliable reasoning.
- Bring expertise in machine learning, AI research, or a closely related technical field to understand how models learn and identify areas where they may fall short.
- Be familiar with LLM training pipelines, evaluation methodologies, and the mechanics of how models develop reasoning capabilities.
- Demonstrate precise, structured thinking skills to effectively translate expertise into high-quality written documentation.
- Exhibit self-directed and reliable work ethic by consistently delivering high-quality work without constant supervision.
- Utilize prior experience in data annotation, data quality assurance, or AI evaluation systems to enhance project outcomes.
- Showcase top-tier Kaggle competition results at Grandmaster or Master level to demonstrate elite-level model understanding and performance optimization.
- Have a background in reinforcement learning, chain-of-thought prompting, or agentic AI systems.
- Engage in working with or evaluating frontier LLMs to contribute to cutting-edge model development.