AI/ ML Engineers

• Key Responsibilities – AI/ML & Automation Engineer (Instantlly)

AI/ML Model DevelopmentDesign, build, and optimize machine learning models for real-world business use cases

• Develop models for prediction, classification, recommendation systems, and NLP tasks
• Build end-to-end ML pipelines for training, validation, deployment, and evaluation
• Create intelligent automation workflows using AI-driven decision systems

Generative AI & LLM DevelopmentDevelop applications using Large Language Models (LLMs)

• Build and maintain RAG (Retrieval-Augmented Generation) pipelines
• Implement prompt engineering, embeddings, vector databases, semantic search, and AI agents
• Fine-tune and optimize LLMs when required
• Develop AI copilots, automated assistants, and conversational workflows for business operations

Business Process Automation for InstantllyAutomate internal business workflows across sales, marketing, customer support, HR, operations, and reporting

• Build AI-powered systems for lead generation, CRM automation, WhatsApp/email automation, and customer engagement
• Develop automated content generation systems for ads, social media, proposals, presentations, and reports
• Create intelligent dashboards, analytics systems, and AI-based decision support tools
• Implement workflow automation using APIs, webhooks, RPA tools, and AI orchestration frameworks
• Build autonomous AI agents capable of handling repetitive operational tasks with minimal human intervention
• Integrate AI systems with existing enterprise platforms, CRMs, ticketing systems, and communication tools

Production Deployment

• Deploy ML and Generative AI models into production using scalable microservices and APIs
• Build inference pipelines with high performance, scalability, and low latency
• Implement monitoring, logging, observability, and model performance optimization
• Ensure production-grade security, reliability, and scalability of AI systems

Data Engineering Collaboration Work with data engineering teams to build robust ML training and inference pipelines

• Ensure clean, high-quality datasets and efficient feature engineering workflows
• Develop data ingestion, transformation, and automation pipelines for AI systems

AI Platform & ArchitectureDesign scalable AI/ML system architectures for high-volume, low-latency environments

• Build centralized AI infrastructure and reusable AI services for Instantlly’s ecosystem
• Integrate AI/ML solutions into enterprise-grade applications and business platforms
• Develop multi-agent AI architectures and automation ecosystems

Research & Innovation Stay updated with the latest advancements in AI, ML, Automation, and Generative AI

• Evaluate and experiment with new frameworks, LLMs, vector databases, and orchestration tools
• Continuously identify opportunities to automate and optimize business operations using AI
• Drive innovation initiatives to improve productivity, reduce manual work, and scale operations efficiently