Research Engineer

Hiring: Staff Research Engineer – Frontier AI, RL & Evaluation

Experience: 7+ Years

Education: Master’s / PhD in AI, ML, Computer Science, or related field

Engagement: 3 Months Contract | Freelance

Location: Remote

Shift: 8 Hours/Day — 7:30 PM to 11:30 PM fixed + 4 flexible hours

LinkedIn Profile: Mandatory in CV

We are looking for a Staff Research Engineer – Frontier AI, RL & Evaluation to work at the intersection of AI research, machine learning, reinforcement learning, evaluation, and research engineering.

The role involves developing research-grade datasets, experiments, prototypes, evaluation frameworks, and tooling for advanced AI systems, with a focus on translating research insights into scalable real-world applications.

Key Responsibilities

• Research capabilities, limitations, training methods, and behavior of frontier AI systems.
• Develop approaches for synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and AI evaluation.
• Design and execute rigorous experiments and analyze results to derive evidence-based technical insights.
• Build research-grade datasets, prototypes, tooling, evaluation frameworks, and AI/ML systems.
• Train, test, and evaluate models using modern machine learning frameworks and tools.
• Work on AI agents, tool-using systems, coding agents, UI/browser-use agents, and MCP-based environments.
• Ensure strong practices around data quality, reproducibility, experimental rigor, and evaluation.
• Collaborate with Research, Engineering, Product, and Operations teams to translate research into scalable solutions.
• Communicate technical findings through reports, publications, technical discussions, workshops, or open-source contributions.
• Mentor engineers/researchers and provide technical leadership across research initiatives.

Requirements

• 7+ years of professional experience with significant research engineering experience in ML, AI, or frontier AI systems.
• Master’s or PhD in Artificial Intelligence, Machine Learning, Computer Science, or a closely related technical field.
• Strong foundations in machine learning with hands-on experience in model training, experimentation, evaluation, or AI system development.
• Research experience in one or more areas:
• Synthetic / Agentic Data Generation
• Reinforcement Learning / Post-Training
• Model Understanding
• AI Evaluation
• Benchmarks
• AI Agents / Tool-Using Systems
• Strong Python programming skills with the ability to rapidly implement, test, and iterate research ideas.
• Experience with modern AI/ML frameworks, research tooling, and evaluation methodologies.
• Strong scientific judgment and understanding of experimental rigor, reproducibility, data quality, and evidence-based analysis.
• Excellent written and verbal communication skills.
• Ability to work independently while collaborating effectively across research and engineering teams.
• Experience mentoring engineers/researchers and providing technical leadership.

If you have strong research engineering experience and want to work on frontier AI, reinforcement learning, agentic systems, and next-generation evaluation, we’d love to hear from you.

Please share your updated CV with your LinkedIn profile included.