Overview

With the intention and conviction of emerging as an unparalleled IT Digital Transformation Services platform, we at Antino Labs are known for providing impeccable software services using cutting edge technology across the globe.

Responsibilities

• Core ML & Engineering :
• Write clean, efficient, and well-documented Python code following OOP principles.
• Build and manage end-to-end ML pipelines : data ingestion, preprocessing, model training, evaluation, and deployment.
• Develop scalable ML systems using frameworks like PyTorch, TensorFlow, and Scikit-learn.
• Generative AI (GenAI) & LLM Systems :
• Design and implement LLM-based applications (chatbots, copilots, automation tools).
• Build and optimize RAG pipelines using vector databases (e.g., FAISS, Pinecone, Weaviate).
• Develop agentic workflows using frameworks like LangChain, LlamaIndex, or similar.
• Implement prompt engineering, structured output generation, and tool/function calling.
• Fine-tune or optimize LLMs using techniques like LoRA, QLoRA, or instruction tuning.
• Work with open-source and proprietary LLMs (e.g., LLaMA, Mistral, GPT, Qwen).
• Software Design & Architecture :
• Design modular, scalable, and maintainable ML and GenAI systems.
• Build APIs and microservices for model serving and GenAI applications.
• Contribute to architectural decisions for AI platforms and products.
• Data Engineering for AI :
• Build data pipelines for feature engineering, transformation, and dataset versioning.
• Manage structured and unstructured data (documents, embeddings, logs).
• MLOps & LLMOps :
• Implement CI/CD pipelines for ML and GenAI systems.
• Manage model and prompt versioning, experiment tracking, and reproducibility.
• Monitor systems for performance, drift, hallucinations, latency, and cost.
• Implement guardrails, evaluation frameworks, and feedback loops for LLMs.
• Performance & Scalability :
• Optimize inference latency and cost for ML and LLM systems.
• Ensure scalability under production workloads (batch + real-time).
• Documentation :
• Create clear documentation for ML models, GenAI pipelines, APIs, and workflows. .