Machine Learning Researcher - Quantitative Finance on Blockchain

Role : Machine Learning Researcher

Location: In Person 5 days in Bangalore office.

About the Role

We are looking for a highly skilled ML Researcher who can take ambiguous, challenging problems and solve them end-to-endfrom problem formulation to deployed models. You'll work on blockchain intelligence and quantitative modeling: think temporal graph networks on transaction flows, behavioral pattern detection, anomaly identification, and predictive modeling on one of the richest, most underexplored datasets in existence.

This is a role for a true problem-solversomeone who goes beyond library usage to design novel approaches, understands the math behind the models, and is obsessed with finding signal in complex data. Prior blockchain or finance experience is a plus, but what we really need is a strong ML researcher who can learn any domain fast and build solutions that work.

We're not just hiring for a rolewe're looking for someone to grow with us. As an early member of our research team, your impact will be outsized, and we reward that accordingly. When your models win, you win.

What We Offer

Generous success-based bonusesyour work directly drives outcomes, and your compensation reflects that.

Growth upsidewe want you invested in what we're building together.

Accelerated career trajectorythis isn't a cog-in-the-machine role; you'll own critical initiatives and grow as the team scales.

High-impact workyour models will inform real decisions in production, not gather dust in a repo.

Autonomy with supportfreedom to explore ideas, with experienced collaborators when you need them.

Key Responsibilities

Own ML research initiatives end-to-endfrom problem definition and data exploration to model design, experimentation, and production deployment.

Design and develop novel ML approaches for behavioral modeling, network analysis, time-series prediction, and anomaly detection on blockchain data.

Run rigorous experimentsformulate hypotheses, design evaluation frameworks, and iterate toward high-performance solutions.

Work with unique data modalitieslarge-scale transaction graphs, on-chain behavioral signals, and real-time streaming data.

Build production-ready modelstranslate research insights into robust, deployed systems that inform real decisions.

Collaborate with quantitative and engineering teams to translate research into actionable strategies.

Stay current with ML researchbring ideas from recent papers into practical application.

Document and communicate findings clearly to both technical and non-technical stakeholders.

Required Qualifications

2+ years of ML experience (including internships, research projects, or publications) with demonstrated ability to solve complex problems from scratch.

Strong foundations in machine learningyou understand why models work, not just how to call them. Comfortable with loss function design, optimization, regularization, and model selection.

Deep hands-on experience with supervised/unsupervised learning, deep learning architectures (transformers, GNNs, sequence models), and classical ML methods.

Strong programming skills in Python and fluency with ML frameworks (PyTorch preferred, TensorFlow, JAX also welcome).

Experience with rigorous experimentationhypothesis-driven development, proper evaluation methodology, and avoiding data leakage.

Ability to work with messy, novel datayou've dealt with data that doesn't come pre-cleaned from Kaggle.

Self-directed problem solveryou can take an ambiguous problem and figure out what to build without detailed specs.

Strong mathematical intuitioncomfortable with probability, statistics, linear algebra, and optimization.

Preferred Qualifications (Nice to Have)

Experience with graph neural networks or network analysis.

Familiarity with time-series modeling or sequence prediction.

Exposure to blockchain data, DeFi, or on-chain analytics.

Background in quantitative finance, trading systems, or financial modeling.

Published research or contributions to ML open-source projects.

Experience with large-scale data processing (Spark, distributed systems).

Familiarity with real-time inference systems and low-latency requirements.

Who You Are

A researcher at heartyou're happiest when you're digging into a hard problem and designing elegant solutions.

A first-principles thinkeryou don't just apply libraries; you understand what's happening under the hood and can build custom approaches when needed.

A fast learnerblockchain and quant finance may be new to you, but you can get up to speed quickly on any domain.

A pragmatic scientistyou balance rigor with shipping; your models work in production, not just in notebooks.

A self-starteryou don't wait for instructions; you identify problems, propose solutions, and run experiments.

Obsessed with signalyou're energized by finding patterns others miss.

Looking to growyou want to build something meaningful, not just collect a paycheck. You're excited by the idea of shaping a team and growing with a company.