Lead II - MLOps

Job Description – MLOps Lead Experience: 10+ Years Location: Any UST Location Employment Type: Full-Time Role Overview UST is looking for an experienced MLOps Lead to design, build, and manage scalable machine learning platforms and production-grade ML workflows. The ideal candidate should have strong expertise in Python, Linux, Bash scripting, MLOps, and CI/CD , with experience leading teams and collaborating with Data Scientists, AI Engineers, and Platform Engineering teams to operationalize machine learning solutions. Key Responsibilities

Design, implement, and manage scalable MLOps platforms and ML deployment pipelines. Develop automation and orchestration solutions using Python and Bash/Shell scripting . Administer and troubleshoot Linux environments supporting ML workloads. Build and maintain CI/CD pipelines for machine learning model deployment and lifecycle management. Automate model deployment, monitoring, retraining, and operational maintenance. Implement monitoring, logging, ing, and performance optimization for ML platforms. Collaborate with Data Scientists, AI Engineers, and Platform teams to streamline ML development and deployment. Ensure platform reliability, security, scalability, and operational excellence. Establish best practices for version control, governance, model promotion, and data management. Perform troubleshooting, root cause analysis, and production support for ML platforms. Mentor junior engineers through technical guidance, code reviews, and knowledge sharing. Drive technical standards, documentation, and continuous improvement across MLOps initiatives.

Required Skills

10+ years of overall IT experience with strong expertise in MLOps and Platform Engineering. Strong programming skills in Python . Hands-on experience with Linux System Administration . Strong scripting experience using Bash/Shell . Experience building automation frameworks and operational tooling. Strong understanding of CI/CD pipelines and deployment automation. Experience with Kubernetes (preferably Amazon EKS) and containerized environments. Experience with Dataiku or similar data science platforms. Knowledge of monitoring, logging, and observability tools. Strong SQL knowledge. Excellent analytical, troubleshooting, and problem-solving skills.

Good to Have

Experience with LLMs, Generative AI, and Agentic AI frameworks. Experience with cloud platforms and Infrastructure as Code (IaC). Knowledge of cost optimization techniques for ML workloads. Experience working in Agile development environments.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field. Relevant certifications in Cloud, Kubernetes, or MLOps are an added advantage.

• Primary Skills: MLOps, Machine Learning, Python, Linux, Bash Scripting, Dataiku, Kubernetes, CI/CD, SQL, Data Science, Agentic AI, Generative AI.

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