[Hiring] AI/ML Engineer @Applabsystems

Role Description

We are seeking an AI/ML Engineer with a strong blend of Full-Stack Software Engineering and Applied AI expertise to design, build, and optimize Generative AI-powered applications. The role involves developing scalable AI solutions, integrating LLMs into enterprise applications, implementing agentic workflows, and delivering secure, production-grade solutions that drive business value.

Key Responsibilities

• Develop and enhance AI-powered features such as chatbots, summarization, knowledge search, and data extraction using LLMs.
• Design and implement RAG (Retrieval-Augmented Generation) solutions, including data preprocessing, embeddings, vector search, and retrieval optimization.
• Build and integrate AI services using OpenAI, Azure AI, and open-source LLMs.
• Develop agentic AI workflows, multi-agent frameworks, and intelligent automation solutions.
• Improve model performance, reliability, and accuracy through prompt engineering, evaluation, guardrails, and fine-tuning techniques.
• Work with vector databases such as FAISS, Pinecone, and pgvector.
• Optimize AI applications for latency, throughput, scalability, and cost efficiency using caching, batching, quantization, and model optimization techniques.
• Collaborate with product, data, and engineering teams to deliver high-quality AI solutions.
• Participate in architecture discussions, code reviews, and knowledge-sharing initiatives.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, AI, or a related field.
• 4–10 years of experience in Applied AI, Machine Learning, Software Engineering, and Digital Transformation.
• Strong experience designing and deploying enterprise-scale AI solutions using Generative AI, LLMs, AI Agents, and Intelligent Automation.
• Proficiency in Python (mandatory) and experience with Java and React JS preferred.
• Hands-on expertise in PyTorch, SQL, OpenAI APIs, FastAPI, Flask, Streamlit, REST APIs, Docker, and modern application architectures.
• Strong understanding of machine learning fundamentals, deep learning, statistics, optimization, feature engineering, and model development.
• Experience with NLP/NLU, semantic search, transformer architectures, embeddings, and model interpretability.
• Knowledge of Azure, AWS, and GCP cloud AI services.
• Ability to communicate technical AI concepts effectively to business and leadership stakeholders.

Preferred Skills

• MLOps, React JS, Java Backend, CI/CD for ML, model monitoring, lifecycle management, Kubernetes, Docker, and JFrog.
• Experience deploying ML models to production environments.
• Distributed ML and scalable data platforms (e.g., Spark).
• Multimodal AI, including Computer Vision and Speech Recognition (ASR).
• Knowledge of AI governance, Responsible AI, security, compliance, and model lifecycle management.
• Experience in healthcare, life sciences, payer/provider, or other regulated industries.
• Experience leading Agile teams and collaborating across cross-functional stakeholders.