ML Quant Engineer

1 week ago

New Delhi, India Conscience AI Labs Full time

About Conscience AI Labs:


Conscience AI, we pioneer a smarter, data-driven approach to investing. Our intelligent system automates portfolio management by tailoring investments to each investor's risk profile. Using a proprietary Financial ML Engine and RL Agentic Workflow, it analyzes 10 million financial parameters to craft dynamic, AI-driven portfolios. It doesn’t just analyze—it adapts, learns, and evolves with each investor’s unique financial journey.



Job Description:


We are looking for a passionate and self-driven ML Quant Engineer Intern who wants to dive deep into financial machine learning and quantitative AI. Ideal candidates will have a deep understanding of machine learning, python programming and statistics, with a focus on financial applications. You'll play a key role in developing, refining, and optimising our investment algorithms, shaping the future of the financial industry.



Responsibilities:


  • Collaborate with our Team of Engineers and financial experts to research & develop, and optimize our portfolio management algorithms.
  • Explore and implement AI agentic workflows: Contribute to developing AI systems that autonomously analyze, adapt, and optimize portfolio management strategies.
  • Reinforcement learning integration: Apply or explore reinforcement learning techniques using libraries like OpenAI Gym, Stable Baselines, or others to enhance the adaptability of investment strategies.
  • Develop advanced statistical models: Implement advanced statistical methods beyond standard algorithms, such as Bayesian optimization, Markov decision processes (MDP), or other stochastic models.



Requirements:


  • Currently in final year or completed a Bachelor’s/Master’s degree in Computer Science, Statistics, Mathematics, or related fields.
  • Proficient in Python, with a keen interest in expanding your RL dynamic programming. 
  • Experience with AI Agentic Framework or willingness to explore frameworks such as Microsoft Autogen or CrewAI.
  • Familiarity with concepts like Modern Portfolio Theory, CAPM, Black-Scholes model, and risk management principles. and basic understanding of financial markets & instruments.
  • Desire to learn and explore statistical models and methods, including, factor analysis, Monte Carlo simulation, Value-at-Risk (VaR), (CVaR) and optimisation libraries in Python like NumPy, SciPy, pandas, CVXPY, PyMC3, Zipline, TA-Lib, PySpark including PyTorch.



Why join us:

  • Inclusive and Open Culture: We value every team member’s ideas equally, regardless of role or title. Your contributions shape our future, and there’s no hierarchy here—just collaboration and innovation.
  • Growth Opportunities: Exceptional performance during the internship could lead to a full-time role, with the potential for ESOPs.

If you are eager to learn, not afraid of challenges, and have a passion for Machine Learning, Reinforcement Learning, Statistics and Financial ML, we would love to hear from you



Interview Stages:


1.Initial Screening & Shortlisting: Selected candidates move to the next stage

2.Technical Assignment: Complete and submit a real-world task within 7 days.

3.Final Round Interview: Discuss your experience and technical skills.


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