Software Engineer II

Tower Research Capital; Gurugram District; On-site; INR 900,000 - 1,500,000; Full time

Benefits offered by this job

Hybrid working opportunities

Generous paid time off

Savings plans and financial wellness

Free breakfast, lunch, and snacks

In-office wellness reimbursements

Company-sponsored sports & fitness

Volunteer opportunities

Social events and learning workshops

Job summary

Tower Research Capital in Gurgaon hires an experienced ML/Data Scientist to build scalable data pipelines, train large-scale models, and push state-of-the-art AI/ML solutions in a fast-paced trading environment.

You will design deep learning architectures, evaluate models, and maintain production ML workflows with a focus on low-latency, reliability, and collaboration across engineering teams.

Qualifications

• Bachelor's, Master's or PhD in CS or related field with 2–6 years of experience.
• Experience training and deploying large-scale deep learning models.
• Experience designing and implementing sequence and time-series models.
• Proficiency in Python with PyTorch or TensorFlow; Git, CI/CD and MLOps.

Responsibilities

• Develop data pipelines to collect, process, and analyze diverse datasets at scale.
• Design and implement deep learning architectures capable of processing large volumes of data.
• Analyze model performance by conducting experiments and tests to evaluate effectiveness.
• Build and manage agentic workflows to support scalable AI/ML solutions.
• Optimize and fine-tune existing machine learning models to improve performance.
• Build and maintain pipelines to monitor and improve production ML models.

Skills

Python

PyTorch

TensorFlow

Deep learning

Time-series models

Git

CI/CD

MLOps

Linux

SQL

Bash scripting

Education

Bachelor's degree in computer science or related field

Master's degree or PhD preferred

Tools

Bash scripting

Job description

Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities.

Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization.

Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.

At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do — combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best

At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.

Responsibilities

• Developing data pipelines to collect, process, and analyze diverse datasets at scale.
• Designing and implementing deep learning architectures capable of processing large volumes of data.
• Analyzing model performance by conducting experiments and tests to evaluate effectiveness and identify opportunities for improvement.
• Building and managing agentic workflows to support scalable and efficient AI/ML solutions.
• Optimizing and fine-tuning existing machine learning models to improve performance and effectiveness.
• Building and maintaining pipelines to monitor, manage, and continuously improve production machine learning and deep learning models.

Qualifications

• A bachelor’s, master’s, or PhD degree in computer science or a related field, with at least 2–6 years of relevant experience.
• Experience training, building, and deploying large-scale deep learning models is required.
• Experience designing and implementing sequence and time-series models is required.
• Expertise in Python, with hands-on experience using deep learning frameworks such as PyTorch or TensorFlow.
• Experience with Git, CI/CD pipelines, and MLOps practices for automating model deployment and managing production machine learning workflows.
• Working knowledge of Linux, SQL, Git, and Bash scripting.

Benefits

Tower’s headquarters are in the historic Equitable Building, right in the heart of NYC’s Financial District and our impact is global, with over a dozen offices around the world.

At Tower, we believe work should be both challenging and enjoyable. That is why we foster a culture where smart, driven people thrive – without the egos. Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win.

• Generous paid time off policies
• Savings plans and other financial wellness tools available in each region
• Hybrid working opportunities
• Free breakfast, lunch, and snacks daily
• In-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more)
• Company-sponsored sports teams and fitness events (JPM Corporate Challenge, Cycle for Survival, Wall Street Rides FAR and more)
• Volunteer opportunities and charitable giving
• Social events, happy hours, treats, and celebrations throughout the year
• Workshops and continuous learning opportunities

At Tower, you’ll find a collaborative and welcoming culture, a diverse team and a workplace that values both performance and enjoyment. No unnecessary hierarchy. No ego. Just great people doing great work – together.

Tower Research Capital is an equal opportunity employer.