ONLY APPLY IF YOU ARE AN IMMEDIATE JOINER AND ARE FINE WORKING ON A 3 MONTH CONTRACT. THESE ARE THE FIRST TWO CRITERIA WHICH WILL BE ASSESSED BEFORE ANYTHING ELSE IN YOUR PROFILE.

Engagement Type: Short Term Contract (3 month)

Start Date: Immediate

Availability: Commitments Required: At least 8 hours per day and minimum 40 hours per week with overlap of 4 hours with PST.

Note: A LinkedIn profile is mandatory for review. Please ensure the resume has the link.

About the Role The client builds large-scale datasets and reinforcement learning environments that power post training for leading AI labs and enterprises. These environments evaluate and improve AI models on complex, long-range, multi-step workflows across high-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, and Customer Experience.

The work includes:

- Software engineering environments for coding agents
- UI environments for computer-use and browser-use agents
- MCP-based environments for function-calling agents across enterprise and consumer applications

We are looking for Staff Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. This role sits at the intersection of research and engineering. You will investigate high-impact questions, design rigorous experiments, build research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications.

You will contribute to areas including synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation.

What You'll Do

Conduct Research on Frontier AI Systems

- Investigate the capabilities, limitations, and training methods of frontier AI systems.
- Formulate research questions that inform the client's products, platforms, and technical strategy.
- Explore current approaches to synthetic and agentic data generation,



reinforcement learning, post-training, model understanding, benchmarks, and evaluation.
- Stay current with advances in machine learning and identify opportunities for meaningful technical contributions.

Build and Evaluate Research Systems

- Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks.
- Train, test, and evaluate models using modern AI and machine learning tools.
- Analyze experimental results and draw clear, evidence-based conclusions.
- Establish strong practices for experimental rigor, data quality, reproducibility, and interpretation.
- Iterate quickly from initial hypotheses to validated technical insights.

Translate Research into Practical Impact

- Collaborate with Research, Engineering, Product, and Operations teams.
- Translate research findings into improvements for the client's products, platforms, and AI capabilities.
- Identify which ideas are ready to move from exploration into scalable, real-world applications.
- Communicate technical findings clearly to both specialized and cross-functional audiences.

Contribute to the Research Community

- Share findings through technical reports, publications, open-source work, workshops, or conferences where appropriate.
- Contribute to the client's research culture through technical discussions, peer review, mentorship, and collaboration.
- Represent the client thoughtfully within the broader AI research community.

What We're Looking For

- PhD or Master's degree in Artificial Intelligence, Machine Learning, Computer Science, or a closely related technical field.



Exceptional equivalent research experience will also be considered.
- Minimum 7+ years of professional experience with significant research engineering experience working on machine learning or frontier AI systems.
- Strong foundations in machine learning and practical experience designing experiments, training models, evaluating models, or developing AI systems.
- Demonstrated research experience in one or more of the following areas:
- Synthetic or agentic data generation
- Reinforcement learning or post-training
- Model understanding
- AI evaluation
- Benchmarks
- AI agents or tool-using systems
- Solid programming skills, particularly in Python, with the ability to implement, test, and iterate quickly in a research environment.
- Experience with modern AI and machine learning frameworks and tooling.
- Strong scientific judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making.
- Excellent written and verbal communication skills.
- Ability to work independently and collaborate effectively across research and engineering teams.
- Experience mentoring engineers or researchers and providing technical leadership.

Evaluation Process (approximately 60 mins) :

- AI interview (20 mins approx)
- Delivery interview (45 - 60 min)

ABOUT US Hyper Lychee Labs is an IT services and consulting company committed to delivering innovative and impactful solutions to a diverse client base, including Fortune 500 companies, the Government of India, and forward-thinking startups. With a focus on leveraging technology for transformation, the company provides custom software development, complex systems implementation, and strategic consulting. Our team of talented professionals collaborates to ensure exceptional results tailored to clients’ needs.

Dedicated to fostering a culture of creativity, diversity, and inclusion, Hyper Lychee Labs strives to empower businesses to thrive in a rapidly evolving world.

📌 Staff Research Engineer - Frontier AI, RL & Evaluation (India)
🏢 Hyper Lychee Labs
📍 India