Roles and Responsibilities:
- With an experience of 8-12 years, play the role of a lead for design, development and implementation of Machine Learning/AI based solutions.
- Work with product managers, lead architects and consultants to understand the requirements and Architecture.
- Ownership of complete module that includes design, development, solutioning and testing of AI/ML module as per requirements while collaborating with respective stakeholders.
- Work as an effective team player, provide training and support to peer and team members in a collaborative manner in the specific areas of specialization.
- Effectively involve in technology research, capability building across newer technologies and tools in Machine Learning / Deep Learning / Artificial Intelligence and Advanced Analytics ecosystem.
- Involve in preparing the Requirement doc, High level, low level Design, White paper and etc.
- Experience with Setting up machine learning problems using Time Series, Anomaly Detection, Natural Language Processing, etc.
- Evaluating performance and efficacy of Machine Learning problems.
- Clarity with Model Lifecycle Management concepts, including concepts of algorithmic risk.
- Very good Hands On experience on Python and Java/Scala programming languages.
- Experience in any of the following frameworks like TensorFlow, Keras2, Pytorch etc.
- Experience on Data modelling, SQL and good hands on with NOSql and ElasticSearch.
- Ability to contribute to multiple projects/demands simultaneously and work in a fast paced, collaborative and iterative environment.
- Strong aptitude, problem solving skills, written communication skills including design documentation, proof of concept and prototype analysis and documentation.
Optional (good to have) skills:
- Decent understanding of NoSQL and prior experience with ElasticSearch Hbase, MongoDB, Cassandra, Cosmos DB, Redis, etc. along with various indexing mechanisms is a plus.
- Familiarity with Machine Learning Services on cloud platforms like Azure, Google Cloud or AWS with GPU based optimization is good to have.
- Experience or familiarity with Big Data frameworks like Spark, Storm, Databricks, Kafka, Zookeeper is a plus.
- Familiarity with Containers (Docker) and Cloud Orchestration Tools (Kubernetes, ECS, EKS) is a plus.