Larsen & Toubro Infotech (LTI) is seeking a Senior Machine Learning Engineer / Architect to design and implement scalable ML applications in production. This role involves operationalizing and monitoring ML models, applying DevOps principles to Machine Learning, and collaborating with data scientists and engineers in a fast-paced environment.
About the role
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
Skills
MlopsAzure MLADFAzure FunctionsPostgresAWSSageMakerGCPDockerJenkinsKubernetesDevOpsPythonSparkRGitBitbucketSQLKubeflowMlflowData WarehousingData Lake