Technology Lead - Data Science Domain

Job Description

Requirements :
 Hands-on experience in implementation and performance tuning of Kinesis, Kafka, Spark or similar implementations.
 Hands-on experience with AWS technology stack and AWS AI stack including AWS Sagemaker and MLOps.
 Experience in Python and Python frameworks (Django, Flask, Bottle), via various IDEs like PyTorch, Jupyter, and Java/. Net, and other open-source libraries, building and designing REST APIs, etc.
 Knowledge of software design patterns/architecture like Micro-services, Layered patterns, etc.
 Passionate teammate who understands and respects personal and cultural differences.
 Ability to work under pressure and be highly adaptable.
 Strong written and communications skills for collaboration with various teams and upper management.
 Solid analytical skills, especially in the area of translating business requirements into technical design with a continuous focus on aligning technical roadmap with the immediate and long-term Business strategy.
 Able to adapt and embrace change and support business strategy and vision.
 Bachelors/Masters or PhD in Computer Science, Physics, Engineering or Math.
 4 - 8 years of total software development and Data platform implementation experience.
 Hands-on experience working on large-scale data science/data analytics projects.
 Experience Implementing AWS services in a variety of distributed computing, enterprise environments.
 Experience with at least one of the modern distributed Machine Learning and Deep Learning frameworks such as TensorFlow, PyTorch, MxNet Caffe, and Keras.
 Experience building large-scale machine-learning infrastructure that has been successfully delivered to customers.
 3+ years experience developing cloud software services and an understanding of design for scalability, performance, and reliability.
 Ability to prototype and evaluate applications and interaction methodologies.

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