TRSS
Overview
Employer Industry: Information Services and Technology Salary up to $163,800. Flexible hybrid work model with the option to work from anywhere for up to 8 weeks per year. Comprehensive benefits package including flexible vacation, mental health days, and wellness resources. Culture focused on inclusion, work-life balance, and social impact initiatives. Opportunity to make a real-world impact by contributing to justice, truth, and transparency. What to Expect (Job Responsibilities)
Build and maintain software that tracks the full lifecycle of machine learning from ideation to post-deployment monitoring Assist in the deployment of machine learning models into production and support these models throughout their lifecycle Build features that help data scientists and AI novices iterate and retrain models efficiently Enable self-service tooling for teams to create and maintain models Continuously challenge and evolve the existing platform capabilities and stay updated with new offerings Required (Qualifications)
Minimum of 5 years in Software Engineering Hands-on experience with public cloud technology (AWS, Azure, GCP) Familiarity with AI concepts and hands-on experience with AI solutions Proficiency in modern programming languages, particularly Python Experience with relational and/or non-relational databases and DevOps practices Preferred Qualifications
Experience with AWS SageMaker, Azure Studio, or similar cloud AI capabilities Hands-on experience with CI/CD in AWS, Git, monitoring, and log analytics We prioritize candidate privacy and champion equal-opportunity employment. Central to our mission is our partnership with companies that share this commitment. If you encounter any employer not adhering to these principles, please bring it to our attention immediately. We are not the EOR (Employer of Record) for this position. Our role in this specific opportunity is to connect outstanding candidates with a top-tier employer.
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Employer Industry: Information Services and Technology Salary up to $163,800. Flexible hybrid work model with the option to work from anywhere for up to 8 weeks per year. Comprehensive benefits package including flexible vacation, mental health days, and wellness resources. Culture focused on inclusion, work-life balance, and social impact initiatives. Opportunity to make a real-world impact by contributing to justice, truth, and transparency. What to Expect (Job Responsibilities)
Build and maintain software that tracks the full lifecycle of machine learning from ideation to post-deployment monitoring Assist in the deployment of machine learning models into production and support these models throughout their lifecycle Build features that help data scientists and AI novices iterate and retrain models efficiently Enable self-service tooling for teams to create and maintain models Continuously challenge and evolve the existing platform capabilities and stay updated with new offerings Required (Qualifications)
Minimum of 5 years in Software Engineering Hands-on experience with public cloud technology (AWS, Azure, GCP) Familiarity with AI concepts and hands-on experience with AI solutions Proficiency in modern programming languages, particularly Python Experience with relational and/or non-relational databases and DevOps practices Preferred Qualifications
Experience with AWS SageMaker, Azure Studio, or similar cloud AI capabilities Hands-on experience with CI/CD in AWS, Git, monitoring, and log analytics We prioritize candidate privacy and champion equal-opportunity employment. Central to our mission is our partnership with companies that share this commitment. If you encounter any employer not adhering to these principles, please bring it to our attention immediately. We are not the EOR (Employer of Record) for this position. Our role in this specific opportunity is to connect outstanding candidates with a top-tier employer.
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