greenhouse
Intern - AI/ML
Tower Research Capital
Gurugram, IND
Intern
Discovered 1 weeks ago
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Responsibilities
- Building and evaluating multi-agent systems, including agent orchestration, tool-calling, and integration with protocols and frameworks such as Model Context Protocol (MCP) and agent skills.
- Implementing agentic coding tools, such as Claude Code, to accelerate development, automate workflows, and build internal tooling.
- Developing and implementing statistical and machine learning algorithms and models to support business and technical requirements.
- Contributing to MLOps practices for deploying, monitoring, and maintaining machine learning models in production environments.
- Analyzing model performance through experiments and testing, while contributing to the optimization and fine-tuning of existing models.
Qualifications
- A bachelor’s, master’s, or PhD degree (ongoing or completed), or equivalent qualification, from a top university, with availability to join an in-office internship for six months starting January 2027.
- Expertise in modern agentic AI tooling is required, including agentic coding assistants such as Claude Code (or similar), building multi-agent systems, and integrating with protocols and frameworks such as Model Context Protocol (MCP) or agent skills.
- Experience training, building, and deploying machine learning models using TensorFlow, PyTorch, or similar frameworks.
- Familiarity with MLOps practices for model deployment, productionization, and lifecycle management.
- Strong knowledge of Python, with hands-on experience using Linux, SQL, Git, and Bash scripting.
- A background in or experience with the finance domain is a plus.
- 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.
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