Women Re-launch - AI Engineer (women only)

Dailoqa; Dadri; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

A financial services firm is seeking a Women AI Engineer to shape the future of their solutions. The candidate will work directly with the founding team to apply the latest AI techniques, focusing on LLM development and innovative AI solutions. Candidates should have a Bachelor's degree in computer science, 2-4 years of experience in MLOps or DevOps, and proficiency in Python and related technologies. This is a unique opportunity to join an early-stage venture dedicated to women's contributions in technology.

Qualifications

• 2-4 years of experience in MLOps, DevOps, or related roles.
• Strong programming experience with Python-based frameworks.
• Familiarity with machine learning concepts and ethical considerations.

Responsibilities

• Build scalable multi-modal LLM-based AI agents.
• Research innovative solutions to AI problems.
• Automate model deployment and monitoring processes.

Skills

Proficiency in Python

Knowledge of machine learning concepts

Strong problem-solving skills

Experience with LLMs

Adaptability

Education

Bachelor's degree in computer science or related field

Tools

PyTorch

Docker

SQLAlchemy

Postgres

Azure

Job description

Overview

Women Re-launch - AI Engineer (women only)

We are looking for Women AI Engineers who want to 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
• 2 - 4 years of experience in MLOps, DevOps, or related roles
• Strong programming experience and familiarity with Python-based deep learning frameworks like PyTorch, JAX, TensorFlow
• Strong familiarity and knowledge of machine learning concepts
• Proficiency in cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code tools like Terraform
• You have experience with technology stack: Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, React.
• Knowledge of data pipeline orchestration tools like Apache Airflow or Prefect
• Familiarity with software testing and test automation practices
• Understanding of ethical considerations in machine learning deployments
• Strong problem-solving skills and ability to work in a fast-paced environment