Job Description

• Bengaluru, Karnataka, India

Strength in Trust

OneTrust is the trust intelligence cloud platform organizations use to transform trust from an abstract concept into a measurable competitive advantage. Organizations globally use OneTrust to enable the responsible use of data while protecting the privacy rights of individuals, implement and report on their cyber security program, make their social impact goals a reality, and create a speak up culture of trust. Over 14,000 customers use OneTrust's technology, including half of the Global 2,000. OneTrust currently ranks #24 on the Forbes Cloud 100 list of top private cloud companies in the world and employs over 2,000 people in regions across North America, South America, Asia, Europe, and Australia.

The Challenge

The MLOps Engineer role is critical because it plays a key role in the successful deployment, management, and monitoring of machine learning models in production environments. At onetrust we are building several ML Model and deployment and operation in a secure, efficient, and effective manner, enabling onetrust to derive maximum value from their machine learning investments.

Your Mission

• Design the data pipelines and engineering infrastructure to support our clients’ enterprise machine learning systems at scale
• Take offline models data scientists build and turn them into a real machine learning production system
• Develop and deploy scalable tools and services for our clients to handle machine learning training and inference
• Identify and evaluate new technologies to improve performance, maintainability, and reliability of our clients’ machine learning systems
• Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
• Support model development, with an emphasis on auditability, versioning, and data security
• Facilitate the development and deployment of proof-of-concept machine learning systems
• Communicate with clients to build requirements and track progress

You Are

• Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or or equivalent
• Experience in MLOps tools like MLFlow or Azure Machine Learning
• Strong software engineering skills in complex, multi-language systems
• Fluency in Python
• Experience working with cloud computing and database systems
• Experience building custom integrations between cloud-based systems using APIs
• Experience developing and maintaining ML systems built with open source tools
• Experience developing with containers and Kubernetes in cloud computing environments
• Ability to translate business needs to technical requirements
• Strong understanding of software testing, benchmarking, and continuous integration
• Exposure to machine learning methodology and best practices
• Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.
• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field
• 5+ years of experience in data engineering or a related field
• Strong analytical skills
• Strong communication and writing skills
• Excellent organizational skills
• 3+ Years experience working with Cloud Platforms (i.e. Microsoft Azure, AWS, GCP)
• 3+ Years experience on Python, Databricks / Hadoop
• 3+ years experience in ML OPS