ML Engineer II

Core Job Responsibilities: • Develop end-to-end ML pipelines encompassing the ML lifecycle from data ingestion, data transformation, model training, model validation, model serving, and model evaluation over time. • Collaborate closely with AI scientists to accelerate productionization of ML algorithms. • Setup CI/CD/CT pipelines for ML algorithms. • Deploy models as a service both on-cloud and on-prem. • Learn and apply new tools, technologies, and industry best practices. Key Qualifications • MS in Computer Science, Software Engineering, or equivalent field • Experience with Cloud Platforms, especially GCP and Azure, and related skills: Docker, Kubernetes, edge computing • Familiarity with task orchestration tools such as MLflow, Kubeflow, Airflow, Vertex AI, Azure ML, etc. • Fluency in at least one general purpose programming language. Python or Java preferred. Strong DevOps skills: Linux/Unix environment, testing, troubleshooting, automation, Git, , dependency management, and build tools (GCP Cloud Build, Jenkins, Gitlab CI/CD, Github Actions, etc.). • Data engineering skills a plus, such as Beam, Spark, Pandas, SQL, Kafka, GCP Dataflow, etc. • 3+ years of experience, including academic experience, in any of the above.

UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world's best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients' organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact—touching billions of lives in the process.