MLOps Engineer

Come work at a place where innovation and teamwork come together to support the most exciting missions in the world! We are looking for a highly motivated Machine Learning Operations Engineer with 3–4 years of experience in building and deploying end-to-end ML products in production environments. The ideal candidate has a strong ML background in Binary/ Multi class Classification, Recommendation Chatbot Applications and deploying training/inference pipelines, with hands-on experience in CI/CD, monitoring, and Kubernetes deployments. Key Responsibilities: · Design, build, and deploy robust ML pipelines for training, fine-tuning, and inference of models (NLP-focused: NER, Classification). · Develop and maintain CI/CD workflows for ML pipelines using Jenkins or similar tools, ensuring rapid and safe deployment to production. · Implement model monitoring and alerting systems to track performance degradation and drift in real-time. · Collaborate with cross-functional teams to retrain models on trigger events and integrate feedback loops into the ML lifecycle. · Hands on with Helm deployment of ML Pipelines in Kubernetes cluster and optimize for scalable and resilient operations. · Use MLflow, Kubeflow, and related tools for experiment tracking, model versioning, and reproducibility. · Write clean, efficient, and scalable code in Python using frameworks such as PyTorch and CUDA. · Experience with tuning, optimising LLM Applications performance in production. Required Skills: · Strong programming experience in Python and PyTorch. · Hands-on experience with CI/CD pipelines using Jenkins. · Proficient with Kubernetes for deploying and managing ML workloads. · Experience with model training, fine-tuning, and inference pipeline development. · Working knowledge of model monitoring and alerting systems (performance drift, latency, accuracy drop). · Experience with MLflow, Kubeflow, and model versioning best practices. · Solid understanding of NER, Text Classification, and common NLP tasks. · Familiarity with CUDA for training models on GPU. Good to Have: · Experience with Generative AI systems in production. · Prior experience with building or deploying applications in Hardwares such as L40S, H100, H200. · Familiarity with LangChain, LangGraph, LangSmith for building LLM-powered agents and applications. Join our talent community and receive the latest Qualys news, content, and be first in line for new job opportunities. Join our Talent Community! Qualys, Inc. (NASDAQ: QLYS) is a pioneer and leading provider of disruptive cloud-based security, compliance and IT solutions with more than 10,000 subscription customers worldwide, including a majority of the Forbes Global 100 and Fortune 100. Qualys helps organizations streamline and automate their security and compliance solutions onto a single platform for greater agility, better business outcomes, and substantial cost savings.