Python AI ML Engineer

Company Description

StockWiz Technologies LLP is a leading trading and investing platform dedicated to empowering traders and investors with state of the art fintech products, world-class education, mentorship, and cutting-edge financial tools. Trusted by over 50,000 traders and investors, the company offers comprehensive support, including trading infrastructure, research, advisory, and funding services. Stockwiz is one of Indias three empaneled algo platforms in the country, along with the largest SEBI registered algo trading platform in India.

With a mission to help individuals achieve financial independence, StockWiz focuses on enhancing skills in the financial markets to facilitate wealth creation for generations to come.

The Role

As an AI/ML Developer at StockWiz, you will join the core team behind StrykeX, our flagship algo trading platform. You wont just be "building models"; you will be architecting the high-performance infrastructure that allows AI to make split-second decisions. You will bridge the gap between complex LLM orchestration (RAG) and robust system engineering.

Key Responsibilities

AI Architecture: Design and implement Retrieval-Augmented Generation (RAG) pipelines to process financial news, filings, and market sentiment into actionable trading insights.

System Design & Fanout: Build scalable fanout architectures to distribute real-time market data and model inferences to thousands of concurrent client sessions.

Performance Optimization: Implement multi-tier caching strategies (Redis, Memcached) to minimize latency in data retrieval and model scoring.

Backend Engineering: Develop high-throughput APIs following strict HTTP/gRPC rules and asynchronous patterns in Python.

Database Management: Optimize database schemas and query performance across relational and Vector Databases (e.g., Pinecone, Milvus, or Weaviate).

Technical Requirements

Expert Python: Deep mastery of asynchronous programming (asyncio), profiling, and memory management.

AI/ML Stack: Proven experience with LangChain/LlamaIndex, PyTorch/TensorFlow, and fine-tuning embeddings for financial contexts.

System Design: Strong grasp of distributed systems, load balancing, and HTTP fanout patterns for real-time data streaming.

Data Persistence: Experience with Caching DB Architecture (Redis/Key-Value stores).Proficiency in SQL and NoSQL environments.Hands-on experience with Vector DBs for RAG.

DevOps: Familiarity with Docker.

Preferred Qualifications

Background in FinTech or Quantitative Trading.

Understanding of WebSockets for low-latency data transmission.

Experience handling "Cold Start" problems in caching layers for live trading signals.

Job Type: Full-time

Pay: 8,00,000 - 14,00,000 per year

Final offer will be based on the conversation, experience and capability of the candidate.

Benefits:

Food provided

Leave encashment

Paid sick time

Work Location: In person