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YOUR TASKS AND RESPONSIBILITIES


Supports the operationalization of AI solutions.
Authors reusable, versioned infrastructure62as62code modules and builds efficient deployment processes aimed at reducing time to market.
Implements monitoring and backup strategies to ensure solution robustness.
Responds to system failures and implements solutions to prevent recurrence.
Proactively contributes to solution architecture discussions by proposing improvements and outlining existing issues.
Scales AI solutions and optimizes them in cloud environments for processing time and cost.
Enhances reproducibility and scalability of AI workflows and builds frameworks for efficient experimentation.
Optimizes the use of version control and CI/CD.
Works closely with Data Scientists and AI Engineers to manage the full lifecycle of AI products with a focus on industrialization and operations.
Participates early in AI product development by formulating and implementing requirements that facilitate deployment and operations.
Contributes to complex projects using generative AI, machine learning, time series forecasting, mathematical optimization, simulation and NLP techniques, integrating multi62layered data models from internal and external sources.

WHO YOU ARE


Master’s or PhD degree with 3 years of experience in DevOps, MLOps, ML/AI Engineering, Software Development or related fields.
Proven educational background or applied experience in at least one of the following: Machine Learning, Statistics, Mathematics, Computer Science or other related quantitative or engineering disciplines.
Proficiency in CI/CD with GitHub Actions, Terraform, solution orchestration and performance tuning.
Proficiency in Docker, GitHub, shell scripting and deploying artifacts in Databricks.
Proficiency in configuring and deploying infrastructure and artifacts in AWS services, with emphasis on Sagemaker, Bedrock, AWS Container Services (ECS, EKS, ECR, Fargate), S3, Lambda, SNS, SQS, Glue and Athena, including necessary v62net configurations.
Good understanding of AWS62native database services such as RDS/Aurora and DynamoDB.
Good understanding of the Linux operating system.
Proven track record in developing advanced analytics products or backend applications within a cloud environment.
Problem62solving and analytical skills.
Experience with at least one of the following (beneficial): machine learning, generative AI, forecasting, mathematical optimization.
Fluent in English, both written and spoken.


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