You will work with: 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 the 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.
Produce complex predictive models and manage the delivery of solutions which can be used to drive measurable client and commercial benefit.
Develop 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.
Experience working with large data sets.
Excellent problem-solving skills.
Strong communication and teamwork.
Familiarity with Financial Services.
Proficiency in English.
Our commitment to diversity & inclusion: We are genuinely passionate about inclusion and we support individuals of all groups; we do not discriminate on the basis of race, religion, gender, sexual orientation, or disability status.
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