AI/ML/Data Engineer building production-grade AI solutions for Bragg's iGaming platform. Collaborating with teams to develop innovative data infrastructures and ML models.
Responsibilities
Develop and build data infrastructure solutions to support the execution of the AI initiatives
Develop data pipelines, workflows and custom data solutions for supporting ML models and scalable AI solutions
Collaborate with the rest of the AI team and the product teams to understand needs, challenges, KPIs, and data, and translate these into effective data and AI products
Design, develop and build scalable ML/AI models
Automatize the code delivery process, model building and serving with CI/CD solutions that can heavily improve and speed-up the AI development cycle
Ensure model performance through continuous monitoring, analysis, and improvement based on product evolution and performance data
Requirements
3+ years of experience in developing, deploying, and scaling data solutions, ML models and AI solutions in a production environment
University degree in Computer Science, ML, AI, Statistics or comparable industry experience
Strong data engineering proficiency with data engineering principles, languages, frameworks, and libraries (e.g., SQL, dbt, data pipeline orchestrators)
Experience in monitoring, analyzing, and improving the performance of ML models in production, and adopting new AI/ML technologies
Experience working with cloud platforms (e.g., GCP) and their AI/ML services
Experience with containerization technologies (e.g., Docker, Kubernetes)
Strong proficiency with AI/ML programming languages, frameworks and libraries (e.g., Python, TensorFlow, PyTorch, scikit-learn)
Familiarity with MLOps practices and tools (e.g., MLFlow) for CI/CD, and monitoring of ML systems
Solid understanding of software engineering principles and best practices
Strong problem-solving and analytical skills
Demonstrated ability to drive projects to completion and work independently
Good communication skills and excellent knowledge of written and spoken English.
Benefits
Experience-based compensation package
Remote or hybrid work model
30 free days
Educational learning opportunities to support each employee's professional growth journey
Sports activities, team building, and informal gatherings
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