AI /ML Engineer

About the Role

We are looking for Women AI Engineers 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

• 2-4 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

Desired

Skills

• 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