NK Securities Research is a leading financial firm that leverages cutting-edge technology, data-driven research, and sophisticated algorithms to trade financial markets. Founded in 2011, we have built deep expertise in high-frequency trading across different asset classes.
We are a fast-growing organization with a strong research and technology culture. The firm’s lean and meritocratic structure enables individuals to work closely with experienced researchers, traders, and engineers, while taking ownership of high-impact problems from an early stage.
Role OverviewWe are looking for an AI/ML Researcher to join our central AI/ML research team in India. This is a research-intensive role suited for individuals who enjoy mathematical problem-solving, experimentation, and working with complex, noisy, high-dimensional datasets. The role will involve close collaboration with quantitative researchers, traders, engineers, and business stakeholders to identify areas where AI/ML can create meaningful value across the firm.
The ideal candidate should be comfortable working on open-ended research problems, converting ideas into structured experiments, and building models that can be evaluated rigorously in real-world settings.
Key ResponsibilitiesAs an AI/ML Researcher, you will:
- Work on our GPU cluster to research and understand the fine-grained behavior of large neural networks and LLM training.
- Fine-tune existing open-source models and build benchmarks to evaluate their performance.
- Explore and analyze large-scale financial market datasets.
- Build ML and statistical models for pattern discovery, prediction, and signal generation.
- Work on short-horizon, noisy, and non-stationary market data.
- Conduct feature engineering, model validation, and performance evaluation.
- Study pricing, market microstructure, and execution-related research problems.
- Convert research ideas into structured experiments with measurable outcomes.
- Collaborate with quantitative researchers, traders, and engineers to translate research into practical use cases.
- Present research findings clearly to technical and business stakeholders.
- Contribute to building reusable research frameworks, tools, and best practices for the AI/ML research function.
We are looking for someone with:
- Strong foundation in mathematics, statistics, probability, linear algebra, optimization, and machine learning.
- Strong programming skills in Python.
- Ability to work with large datasets, run experiments, and interpret results rigorously.
- Strong analytical and problem-solving ability.
- Comfort with ambiguity, open-ended problems, and iterative research.
- Ability to independently structure research problems and drive them to conclusion.
- Curiosity to learn new domains, ask thoughtful questions, and challenge assumptions.
- Strong communication skills to explain research outcomes clearly.
- Python, NumPy, Pandas, Scikit-learn
- Machine learning, deep learning, and time-series modelling
- Probability, statistics, and optimization
- LLMs, neural networks, model fine-tuning, and benchmarking
- Research-oriented problem solving
- Experience with Kaggle, research projects, trading datasets, ML competitions, or large-scale data problems
- Prior exposure to financial markets, quantitative research, or market microstructure is a plus, but not mandatory
- Opportunity to be part of a central AI/ML research team being built within a research-driven trading firm.
- Work on real-world, high-impact problems involving complex and evolving datasets.
- Collaborate closely with experienced quantitative researchers, traders, and engineers.
- Strong ownership from an early stage.
- Exposure to research problems across AI/ML, quantitative finance, market microstructure, pricing, and execution.
- Fast-paced, meritocratic environment with significant learning and growth opportunities.
Skills Required
- Strong foundation in mathematics, statistics, probability, linear algebra, optimization, and machine learning.
- Strong programming skills in Python.
- Experience working with GPU clusters for model training and experimentation.
- Ability to work with large datasets, run experiments, and interpret results rigorously.
- Experience in feature engineering, model validation, and performance evaluation.
- Strong analytical and problem-solving ability; comfort with ambiguity and open-ended research.
- Ability to independently structure research problems and drive them to conclusion.
- Strong communication skills to present research clearly to technical and business stakeholders.
- Experience with Python libraries and tools such as NumPy, Pandas, Scikit-learn.
- Experience with deep learning, LLMs, model fine-tuning, benchmarking, and time-series modelling.
- Prior exposure to financial markets, quantitative research, or market microstructure.
- Participation in ML competitions or large-scale research projects (e.g., Kaggle) or similar experience.
What We Do
NK Securities Research is a leading financial firm that leverages cutting edge technology and sophisticated algorithms to trade the financial markets. Founded in 2011, we have gained invaluable experience in the field of High Frequency Trading across different asset classes








