Job Description - AI/ML Researcher

 


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 Overview


We 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 Responsibilities


As 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.


Ideal Candidate Profile


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.


Preferred Skills



  • 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


Why Join Us



  • 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.


 

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