Senior MLOps Engineer
- Bangalore, Karnataka
- Permanent
- Full-time
- Can build scalable MLOps platform and work with business architects to implement and expand the MLOps set up
- Has worked on deploying an ML model to production and has worked on model monitoring, inferencing, drift concepts, feature stores etc. for a project
- Has good understanding of how ML algorithms work and how to debug in case of any issues in the code
- Has deployed an application using container and container orchestration
- Manages conversation with the client stakeholders to understand the requirement and translate it into technical outcomes
- Responsible for bridging the gap between machine learning and software engineering, focusing on the deployment, scaling, and management of machine learning models in production environments
- Is a developer who is focused on streamlining the process of developing, deploying, and maintaining machine learning systems, ensuring they are efficient, scalable, and reliable
- Has strong conceptual understanding of ML lifecycle and different ML algorithms
- Has worked on at least one cloud platform and related ML as a Service platform
- Has strong understanding of DevOps practices and is skilled to develop end-end CI/CD pipelines
- Has strong execution knowledge of Data Modeling, Databases in general (SQL and NoSQL), software development lifecycle and practices, unit testing, functional programming, etc.
- Has experience in one of the ML as a service platform, such as Azure devops, DataikuI (or equivalent open-source)
- Proficient in at least one programming language used in data engineering, such as Python
- Has strong snowflake knowledge
- Has worked on at least one cloud platform
- Business Understanding
- Logical thinking and problem-solving skills along with an ability to collaborate
- Ability to analyze problems and develop actionable and appropriate tactical plans quickly
- Has good managerial skills and can lead a team
- Good at verbal and written communication
- Has good stakeholder management skills
- Exercises independent judgment within defined practices and procedures to determine appropriate action
- Demonstrated ability to provide mentorship to junior
- Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras
- Proficiency in natural language processing (NLP) techniques and tools
- Knowledge of computer vision and image processing algorithms
- Experience with large-scale data processing and distributed computing frameworks like Apache Spark
- Familiarity with data engineering and data manipulation techniques
- Ability to work with big data technologies like Hadoop or Apache Kafka
- Ability to communicate complex concepts to both technical and non-technical stakeholders