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2 Days ago

Senior AI Engineer

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1100000 - 1500000 INR - Yearly
Bangalore, KA, India
Information Technology
Full-Time
Aris Investing

Overview

*About Aris Investing: *

Aris Investing LLC is a dynamic and innovative investment management firm specializing in technology-enabled sub- advisory services. We empower financial advisors to optimize client portfolios for personalized and efficient growth through cutting-edge machine learning and quantitative techniques. Job Description: Aris Investing is seeking a talented and motivated Machine Learning and Quantitative Analyst with 1-3 years of experience in applying machine learning or other quantitative techniques using Python, specifically in the financial domain. The ideal candidate will have a strong background in optimization techniques and a passion for leveraging data- driven insights to enhance investment strategies.

Key Responsibilities

Design, develop, and deploy AI/ML solutions for financial and operational use cases.
Build and optimize LLM-powered applications, AI agents, RAG systems, and workflow automation tools.
Develop predictive models, recommendation engines, and intelligent data-processing pipelines.
Integrate AI models with web applications, APIs, and internal systems.
Work with structured and unstructured financial data to generate actionable insights.
Evaluate emerging AI technologies and identify opportunities for implementation across the organization.
Establish best practices for model deployment, monitoring, security, and performance optimization.
Mentor junior engineers and contribute to technical decision-making.

Must-Have Skills

Python Programming – Strong software engineering fundamentals and backend development.
Machine Learning & Deep Learning – Model development, training, evaluation, and deployment.
Large Language Models (LLMs) – Experience with OpenAI, Anthropic, Llama, etc.
RAG & AI Agent Development – Building knowledge retrieval systems and autonomous workflows.
Cloud & Production Deployment – AWS/Azure/GCP, APIs, Docker, and scalable deployments.
Data Engineering & Databases – SQL, vector databases, data pipelines, and handling large datasets.

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