Explore and try out exciting upcoming libraries, models, technologies to analyze and recommend the best one for the team
Design and implement scalable ML and DL systems, products, and solutions.
Collaborate with engineering and DevOps teams to build and deliver systems that can be deployed both in the cloud and on premise, e.g., using Azure, Docker, and Kubernetes.
Build deep learning-based products on CPUs and GPUs, leveraging latest deep learning and machine learning libraries.
Develop and evaluate data analytics models, algorithms, systems and solutions using a variety of advanced data science techniques
Produces complex predictive models and manages the delivery of solutions which can be used to drive measurable client and commercial benefit
Develops a solid understanding of data structures and business in order to extract and integrate required data sources for analysis
Key requirements
Excellent programming skills: Experience in languages such as Python
1-2 years of relevant experience
You have experience with both machine learning and building software
You have experience with databases
Machine learning domain knowledge—bias-variance tradeoff, exploration/exploitation—and understanding of various model families, including neural net, decision trees, Bayesian models, instance-based learning, association learning, and deep learning algorithms
Good understanding in Deep Learning
Familiarity with Azure cloud ecosystem and OpenAI models