Posted:4 days ago|
Platform:
On-site
Full Time
Build and Maintain software that tracks the full lifecycle of ML from ideation to post deployment monitoring
Assist in the deployment of machine learning models into production and support these models throughout their lifecycle, including GenAI models
Build out features that help data scientists and AI novices to iterate and re-train models at speed and ease.
Build out features that facilitate the data collection and annotation for non-structured data and NLP use cases
Utilize a variety of software and tools both commercial and open source
Enable self-service tooling for teams to create and maintain models
Create and deploy tooling for model monitoring and model governance
Be part of a model ops framework
Continuously challenge and evolve the existing platform capabilities and keep up to date with new offerings
5 years in Software Engineering
Hands-on experience working with public cloud technology (AWS, Azure, GCP)
Ability to collaborate with scientists, product management and work with an engineering-focused, iterative team to build and establish product requirements.
Comfortable building prototypes from scratch.
Familiarity with AI concepts and hands on experience with AI solutions
Experience with AWS sagemaker, Azure Studio or similar cloud AI capabilities
Proficiency in modern programming languages and in particular Python
Experience with relational and/or non-relational databases
Experience with Agile development and delivery - Scrum, Lean, XP, Kanban methodologies.
Deep understanding of computer science concepts, such as time and space complexity, data structures and basic algorithms.
Experience building ETL data pipelines.
Hands on DevOps experience - CI/CD in AWS, Git, Monitoring, Log Analytics
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