onsite
Lead, AI Engineering & SDLC Automation - agilent
Software Engineer
Lead AI Engineering and SDLC Automation, driving end‑to‑end AI solutions, model deployment, and automation pipelines using Python, ML frameworks, and cloud services.
About the role
Key Responsibilities
- Lead the AI Engineering team to design, develop, and deploy scalable machine learning models across the organization.
- Own the full software development lifecycle, from data ingestion and feature engineering to model training, validation, and production deployment.
- Build and maintain CI/CD pipelines and MLOps workflows that automate model testing, monitoring, and rollback.
- Implement containerized microservices using Docker and orchestrate with Kubernetes.
- Integrate AI services with cloud platforms (AWS/GCP/Azure) and manage infrastructure as code.
- Conduct performance tuning, scalability testing, and cost optimization, and lead incident response for model drift and data quality issues.
Requirements
- Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch).
- Experience with MLOps tools (MLflow, Kubeflow, SageMaker) and CI/CD pipelines.
- Deep understanding of DevOps practices, containerization, and cloud services (AWS, GCP, Azure).
- Excellent problem‑solving, communication, and leadership skills.
Skills
pythonmachine learningmlopsdockerkubernetesawscicd