24-MAG
2 - 10 employees
🤝 B2B
💼 Consulting
B2B • Consulting
24-MAG is a commercial strategy and execution firm that helps B2B organizations design and implement systems, workflows, and operating rhythms for sales, client management, and cross-functional projects. They focus on transforming scattered processes into aligned, measurable, and scalable commercial functions—covering pipeline structure, account management frameworks, and operational discipline for teams seeking efficient, intentional growth.
Machine Learning Research Engineer
Job not on LinkedIn
🔥 3 minutes ago
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24-MAG
2 - 10 employees
🤝 B2B
💼 Consulting
B2B • Consulting
24-MAG is a commercial strategy and execution firm that helps B2B organizations design and implement systems, workflows, and operating rhythms for sales, client management, and cross-functional projects. They focus on transforming scattered processes into aligned, measurable, and scalable commercial functions—covering pipeline structure, account management frameworks, and operational discipline for teams seeking efficient, intentional growth.
📋 Description
• Turn practical ML research ideas into well-defined, multi-step evaluation tasks • Develop assignments involving model training, experimental modifications, and performance analysis • Define clear technical requirements, expected outputs, and success criteria • Ensure tasks assess genuine implementation and experimental reasoning rather than superficial library usage • Implement reference solutions using Python, scripts, and notebook environments • Configure and run model-training experiments from setup through final evaluation • Modify model components, training procedures, reward functions, or experimental parameters • Validate code, dependencies, datasets, intermediate outputs, and final results • Document complete workflows so experiments can be reproduced independently • Review how frontier AI models approach complex machine learning tasks • Assess implementation quality, experimental methodology, and technical conclusions • Identify coding errors, unsupported assumptions, weak experimental controls, and misleading interpretations • Develop selected tasks involving reinforcement learning fundamentals • Evaluate reward-function changes, policy-training behaviour, and experimental outcomes • Work closely with researchers, task authors, and fellow machine learning specialists
🎯 Requirements
• At least 1 year of experience in machine learning research, research engineering, or a comparable technical role • Hands-on experience training and evaluating ML models through complete experimental workflows • Strong understanding of experiment setup, execution, analysis, and reproducibility • Familiarity with large language model capabilities, limitations, and evaluation techniques • Working proficiency in Python and Git • Comfort using both scripting and notebook-based environments • Strong technical writing, analytical reasoning, and attention to detail • Ability to work independently through ambiguous, open-ended research problems • Reliable availability for approximately 35 hours per week
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