Company Description:

Curvia AI is a London, UK-based technology and AI solutions company that transforms complexity into opportunity through enterprise solutions, AI-powered automation, and data-driven insights. We build practical, scalable, and human-centred years of technology grounded in integrity, security, and responsible innovation.

Role Overview:

We are building large-scale datasets and reinforcement learning environments that power post-training for leading AI labs and enterprises. Our 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.

Our 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 AI 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.

Offer Details:

- Pay: US $125/day
- Commitments Required: At least 8 hours per day and a minimum of 40 hours per week, with an overlap of 4 hours with PST.
- Mode of Work: Fully Remote
- Number of positions: 10
- Years of experience: 7+ years

What You'll Do Day-to-Day:





Conduct Research on Frontier AI Systems:

- Investigate the capabilities, limitations, and training methods of frontier AI systems.
- Formulate research questions that inform Turing’s products, platforms, and technical strategy.
- Explore new 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.
- Analyse experimental results and draw clear, evidence-based conclusions.
- Establish strong practices for experimental rigour, 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 Turing’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 specialised 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 Turing’s research culture through technical discussions, peer review, mentorship, and collaboration.
- Represent Turing 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
- Strong programming skills, particularly in Python, with the ability to implement, test, and iterate quickly in a research workplace.
- Experience with modern AI and machine learning frameworks and tooling.
- Strong scientific judgment around experimental rigour, 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)

📌 AI Research Engineer (India)
🏢 Curvia AI
📍 India