Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!
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.
Skills Required
- 2-3 years of experience in building and deploying ML products
- Strong programming experience in Python
- Hands-on experience with CI/CD pipelines using Jenkins
- Proficient with Kubernetes for deploying ML workloads
- Experience with model monitoring and alerting systems
- Experience with MLflow, Kubeflow, model versioning best practices
- Solid understanding of NER and Text Classification
- Familiarity with CUDA for training models on GPU
Qualys Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Qualys and has not been reviewed or approved by Qualys.
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Affordable Benefits — Benefits costs are widely viewed as low for employees and dependents, with healthcare often described as almost fully paid for. Feedback suggests this affordability helps offset perceptions of lower base pay in some roles.
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Healthcare Strength — Healthcare offerings are broad, including multiple medical plan options, dental and vision coverage, mental health support, and disability insurance. Benefits are described as “pretty amazing” or “great,” reinforcing perceived quality and coverage depth.
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Equity Value & Accessibility — Equity participation is accessible through company stock plans and an employee stock purchase plan. Compensation packages commonly include equity alongside salary and bonus, which some consider a meaningful part of total rewards.
Qualys Insights
What We Do
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. The Qualys Cloud Platform leverages a single agent to continuously deliver critical security intelligence while enabling enterprises to automate the full spectrum of vulnerability detection, compliance, and protection for IT systems, workloads and web applications across on premises, endpoints, servers, public and private clouds, containers, and mobile devices. Founded in 1999 as one of the first SaaS security companies, Qualys has strategic partnerships and seamlessly integrates its vulnerability management capabilities into security offerings from cloud service providers, including Amazon Web Services, the Google Cloud Platform and Microsoft Azure, along with a number of leading managed service providers and global consulting organizations. For more information, please visit http://www.qualys.com
