Saksham Verma

Software Engineer

Dehra Dun, Uttarakhand, India1 yr 10 mos experience

Most Likely To Switch

Key Highlights

Expert in machine learning and quantitative finance.
Proven track record in developing trading strategies.
Strong backend development skills with modern technologies.

Stackforce AI infers this person is a Fintech and Machine Learning expert with strong backend development capabilities.

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Skills

Core Skills

Back-end Web DevelopmentSoftware DevelopmentQuantitative ResearchMachine LearningResearch

Other Skills

BacktraderC (Programming Language)C++CI/CDCNNData AnalysisData StructuresDatabase Management System (DBMS)Deep LearningDockerFastAPIGinGo (Programming Language)GrafanaGraph Networks

About

I am fascinated by how we can solve problems by translating logic into code. The more challenging the problem, the more determined I become—I thrive on complexity and enjoy pushing my limits. I have experience in both quantitative finance research and software development, having worked as a Quantitative Machine Learning Research Intern at Trexquant and currently working as a Software Engineer at Blinkit. My primary interests lie in machine learning and deep learning, with a particular passion for graph-based learning models. I am always open to opportunities that challenge me in the fields of machine learning, software development, or quantitative finance. If you’d like to connect or discuss exciting challenges, feel free to reach out at saksham0109@gmail.com.

Experience

1 yr 10 mos

Total Experience

11 mos

Average Tenure

1 yr 5 mos

Current Experience

Blinkit

2 roles

Software Engineer

Jun 2025 – Present · 1 yr · Gurugram, Haryana, India

Software Engineer Intern

Jan 2025 – Jun 2025 · 5 mos · Gurugram, Haryana, India

> Worked on backend development using Python (FastAPI) and Go (Gin), designing and optimizing APIs for logistics and supply chain operations.
> Gained hands-on experience with Docker, Kubernetes, Grafana, and CI/CD pipelines, contributing to scalable and efficient system deployments.

Python (Programming Language)FastAPIGo (Programming Language)DockerKubernetesGrafana+3

Trexquant investment lp

Quantitative Research Intern

May 2024 – Jul 2024 · 2 mos · Gurugram, Haryana, India · On-site

> Designed and engineered mid-frequency trading signals (alphas) for Futures and US Equity markets, leveraging statistical arbitrage techniques to achieve outstanding live trading performance.
> Applied advanced machine learning models to predict asset returns following Earnings Announcements, incorporating a novel feature to enhance the strategy’s effectiveness and profitability.
> Developed and productionized novel data variables using high-frequency options and stock data, enabling more informed trading decisions and enhancing predictive accuracy.

Statistical ArbitrageMachine LearningPython (Programming Language)Quantitative Research

Mit media lab

Research Intern

Nov 2023 – Apr 2024 · 5 mos · Remote

> Collaborated with Dr. Samantha Chan to develop a real-time classification model using pupil and EmotiBit sensor data.
> Performed extensive data analysis to extract meaningful patterns and features from physiological signals.
> Designed, implemented, and optimized LSTM and CNN-based deep learning models to accurately classify the data in real time.

Data AnalysisDeep LearningLSTMCNNMachine LearningResearch

William o'neil india

Quantitative Research Intern

May 2023 – Jul 2023 · 2 mos · Remote

> Conducted research on leveraging yield curve inversion data to generate trading signals for fixed assets
> Designed, implemented, and backtested trading strategies using the Backtrader framework in Python
> Achieved performance that outperformed the S&P 500 with our strategy.

Python (Programming Language)BacktraderQuantitative Research