Assess requirements necessary for developing ML services in the Support Delivery domain.
Develop and optimize state-of-the-art machine learning algorithms that provide robust situational assessment and predictive capabilities.
Explore, understand, and implement most recent AI technologies, like Large Language Models, Generative AI, etc.
Design and develop large scale training and deployment systems, using multiple GPU’s and servers, dedicated H/W, multi-threading, and parallelization.
Collaborate with data engineers to develop data and model pipelines.
Be able to comfortably handle and analyze real-world data sets.
Strive for automation and cloud operation readiness.
Improve quality and system scalability through continuous evaluation, analysis, and refinement of the system implementation.
Requirements & Skills:
University degree in Computer Science, Statistics, Data Science, or a related technical field
Strong analytical and problem-solving skills with a passion for Machine Learning
Solid foundation in computer science, with strong competencies in algorithms, data structures, object-oriented programming, design patterns, multi-threaded programming, and software design principles
Knowledge of programming languages, preferably Python
Experience with at least one of the following cloud-related technologies & concepts: Kubernetes, Docker, Kubeflow or other IaaS/PaaS environments
Extensive knowledge in building, validating and evaluating machine learning models, as well as experience in machine learning evaluation metrics and best practices
Practical experience in architecting, training and analyzing deep learning models
Hands-on experience in working with big-data and SQL/no-SQL technologies such as PostgreSQL, Spark, Redis, ElasticSearch
Fluent in English, both verbal and written communication skills
Creative thinking, willingness and ability to learn quickly new concepts and technologies
Strong team player
Experience with version control tools such as git
Experience handling real-world large-scale data sets
Familiar with modern DevOps methodologies and ability to establish CI/CD process
Experience with Agile
5+ years of development experience, including 3+ years of commercial/academic machine-learning experience
