Senior AI / ML Solutions Engineer

Years of Experience : 4-8 Yrs

About the Role

We are looking for AI and Machine Learning engineer who want to help shape the future of Financial Services clients and our company. As part of the team, you will get to

Work directly with our founding team and be a core member.

Apply the latest AI techniques to solve real problems faced by Financial Services clients.

Design, build, and refine datasets to evaluate and continuously improve our solutions.

Participate in strategy and product ideation sessions, influencing our product and solution roadmap.

Key Responsibilities

Agentic AI Development : Work on building scalable multi-modal Large Language Model (LLM) based AI agents, leveraging frameworks such as LangGraph, Microsoft Autogen, or Crewai.

AI Research and Innovation : Research and build innovative solutions to relevant AI problems, including Retrieval-Augmented Generation (RAG), semantic search, knowledge representation, tool usage, fine-tuning, and reasoning in LLMs.

Technical Expertise : Proficiency in a technology stack that includes Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, and React.

LLM and NLP Experience : Hands-on experience working with LLMs, RAG architectures, Natural Language Processing (NLP), or applying Machine Learning to solve real-world problems.

Dataset Development : Strong track record of building datasets for training and / or evaluating machine learning models.

Customer Focus : Enjoy diving deep into the domain, understanding the problem, and focusing on delivering value to the customer.

Adaptability : Thrive in a fast-paced environment and are excited about joining an early-stage venture.

Model Deployment and Management : Automate model deployment, monitoring, and retraining processes.

Collaboration and Optimization : Collaborate with data scientists to review, refactor, and optimize machine learning code.

Version Control and Governance : Implement version control and governance for models and data.

Required Qualifications :

Bachelor's degree in computer science, Software Engineering, or a related field

4-8 years of experience in MLOps, DevOps, or related roles

Have strong programming experience and familiarity with Python based deep learning frameworks like Pytorch, JAX, Tensorflow

Have strong familiarity and knowledge of machine learning concepts

Proficiency in cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code tools like Terraform