Data Science Engineer Intern

Eshal.ai is building an enterprise AI platform that enables businesses to deploy, manage, and orchestrate intelligent digital employees across customer service, operations, and back-office functions.
We are looking for a ML / AI Engineer with strong Python experience to help us build the intelligence behind Eshal's AI agents and enterprise automation platform.
This is a hands-on engineering role. You will work on AI/ML capabilities, LLM integrations, RAG pipelines, agent workflows, APIs, and production systems.

What You’ll Do
Build and integrate AI/ML capabilities using Python.
Develop and improve LLM-powered applications and AI agents.
Build and maintain RAG pipelines, including document processing, chunking, embeddings, retrieval, and reranking.
Work with LLM APIs and open-source models.
Design prompts, system instructions, evaluation frameworks, and AI workflows.
Develop AI services and APIs that can be integrated into production applications.
Work with vector databases and search technologies.
Evaluate AI responses for accuracy, relevance, consistency, latency, and cost.
Build workflows for context, memory, tool use, and agent orchestration.
Work with structured and unstructured data to improve AI performance.
Develop data and evaluation pipelines for continuously improving AI systems.
Integrate AI capabilities with business systems such as CRM, ERP, knowledge bases, communication platforms, and other APIs.
Monitor and troubleshoot AI systems in production.
Optimize AI applications for performance, reliability, scalability, and cost.
Write clean, maintainable, and well-tested Python code.
Work closely with backend, frontend, QA, DevOps, and product teams.
Stay current with developments in LLMs, agentic AI, RAG, and machine learning.

Required Skills

Python & Software Engineering
Strong hands-on experience with Python.
Good understanding of object-oriented programming and software design.
Experience building APIs and backend services.
Familiarity with FastAPI, Flask, or Django.
Experience with Git and collaborative software development.
Understanding of testing, debugging, logging, and error handling.

AI / ML
Good understanding of Machine Learning and AI fundamentals.
Practical experience working with LLMs.
Experience with LLM APIs such as OpenAI, Anthropic, Gemini, or similar.
Understanding of:
Prompt engineering
Embeddings
Vector search
RAG
Context management
AI evaluation
Model selection
Familiarity with libraries/frameworks such as LangChain, LlamaIndex, Hugging Face, or similar is a plus.
Experience with Pandas, NumPy, and Scikit-learn.

Data & Infrastructure
Good understanding of SQL and databases.
Familiarity with PostgreSQL, MongoDB, Redis, or vector databases.
Basic understanding of Docker and cloud environments.
Familiarity with asynchronous processing and distributed systems is a plus.

Good to Have
Experience building AI agents or agentic workflows.
Experience with RAG systems in production.
Experience with vector databases such as Pinecone, Qdrant, Weaviate, pgvector, or similar.
Experience with model evaluation and LLM observability.
Experience with fine-tuning or adapting open-source models.
Experience with PyTorch or TensorFlow.
Experience with Kubernetes and CI/CD.
Experience integrating AI with CRM, ERP, WhatsApp, email, voice, or other communication platforms.
Experience working on SaaS or enterprise AI products.

What We’re Looking For
We are looking for someone who is not only familiar with AI concepts but can actually build and ship
AI features.
You should be someone who:
Enjoys solving complex technical problems.
Can take an AI idea from prototype to production.
Understands that production AI requires more than simply calling an LLM API.
Can investigate issues and find solutions independently.
Writes clean and maintainable Python code.
Is comfortable learning new AI technologies quickly.
Thinks about accuracy, latency, scalability, security, and cost.
Takes ownership of work and follows tasks through to completion.
Enjoys working in a fast-moving startup environment.

What You’ll Work On at Eshal
You will have the opportunity to work on real-world AI systems including:
AI Agents → RAG → Knowledge → Memory → Tools → APIs → Enterprise Integrations → Omnichannel Experiences

You may work on areas such as:
AI Concierge and digital employees
Knowledge and RAG systems
Multi-agent workflows
Conversation intelligence
Customer context and memory
Tool calling and agent actions
LLM evaluation
AI guardrails
Enterprise AI integrations
AI performance and observability

What We Offer
Remote-first working environment.
Flexible working hours.
Hands-on experience building production AI systems.
Exposure to LLMs, AI agents, RAG, and enterprise AI.
High ownership and opportunity to influence the product.
Close collaboration with the founding and engineering team.
Competitive compensation based on experience and skills.
ESOP opportunity for eligible permanent employees.