Job Summary
We’re looking for a Senior Machine Learning Engineer / Architect who is experienced in designing and implementing ML applications at scale in production for our AI Engineering team. The team is a cross-functional team and has Software Engineers and ML Engineers and closely works with data scientists and data engineers in operationalizing ML models.
Roles and Responsibilities
- As a Senior ML Engineer, you will be a key stakeholder and owning responsibility in designing and architecting end to end ML solutions
- Operationalize and monitor machine learning models using high end tools and technologies.
- Design & implementation of DevOps principles in Machine Learning
- Data Science quality assurance and testing
- Model Governance and Monitoring
- Execute best practices in version control and continuous integration / delivery
- Collaborate with data scientists, engineers and other key stakeholders
- Work well in a fast-paced cross-functional environment
Skills/Requirements
- Minimum 5+ years of experience in AI/ML
- Experience in implementing machine learning life cycle on AWS (Using Sage Maker) or Azure (Azure ML) or GCP other cloud platforms
- Experience with Docker, Jenkins, Kubernetes, and other DevOps tools.
- Good Programming skills (at least one of Python/Spark/R).
- Experience with Machine learning frameworks, libraries and agile environments.
- Experience with version control tools such as Git, Bitbucket etc.
- Experience with SQL and databases.
- Familiarity with Kubeflow or mlflow
- Understanding of Data Warehousing and data Lake concepts would be plus
- Very Strong communication skills
- Outstanding analytical and problem-solving skills