Role Description
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.
Skills
mlops,machine learning,python,bash scripting,linux,dataiku,kubernetes,sql,agentic ai,cicd,data science