[Remote] ML/MLOps Engineer (Python, AWS)
Note: The job is a remote job and is open to candidates in USA. Sphere is an insurance technology company seeking a ML/MLOps Engineer to contribute to production-grade AI systems. The role involves developing, maintaining, and deploying Python-based services, building ML pipelines, and ensuring the reliability and performance of AI applications.
Responsibilities
⢠Develop, maintain, and deploy Python-based production services
⢠Build and operate ML pipelines and MLOps infrastructure
⢠Work with AWS services including Lambda, Step Functions, DynamoDB, Kafka, and containerized applications
⢠Deploy, monitor, and maintain ML models (e.g., XGBoost) in production environments
⢠Ensure reliability, correctness, and performance of AI systems
⢠Ship code to production frequently (daily or near-daily)
⢠Debug and resolve production issues efficiently
⢠Collaborate with data scientists, product managers, and operational teams to support AI-driven products
Skills
⢠Experience with Python (production-quality code)
⢠Hands-on AWS experience (Lambda, Step Functions, DynamoDB, IAM, containers)
⢠Experience with Kafka or other event-driven systems
⢠Experience deploying ML models to production
⢠Git / CI/CD experience
⢠Experience with MLOps platforms and automation tools
⢠Real-time data pipelines
⢠Experience with AI chatbots or retrieval-augmented generation (RAG) systems
Company Overview
⢠Drive your sustainable digital transformation with focus on innovation and scale It was founded in 2004, and is headquartered in Chicago, Illinois, USA, with a workforce of 201-500 employees. Its website is http://sphereinc.com.
Company H1B Sponsorship
⢠Sphere has a track record of offering H1B sponsorships, with 3 in 2021, 1 in 2020. Please note that this does not guarantee sponsorship for this specific role.
Apply Now
Apply Now
Responsibilities
⢠Develop, maintain, and deploy Python-based production services
⢠Build and operate ML pipelines and MLOps infrastructure
⢠Work with AWS services including Lambda, Step Functions, DynamoDB, Kafka, and containerized applications
⢠Deploy, monitor, and maintain ML models (e.g., XGBoost) in production environments
⢠Ensure reliability, correctness, and performance of AI systems
⢠Ship code to production frequently (daily or near-daily)
⢠Debug and resolve production issues efficiently
⢠Collaborate with data scientists, product managers, and operational teams to support AI-driven products
Skills
⢠Experience with Python (production-quality code)
⢠Hands-on AWS experience (Lambda, Step Functions, DynamoDB, IAM, containers)
⢠Experience with Kafka or other event-driven systems
⢠Experience deploying ML models to production
⢠Git / CI/CD experience
⢠Experience with MLOps platforms and automation tools
⢠Real-time data pipelines
⢠Experience with AI chatbots or retrieval-augmented generation (RAG) systems
Company Overview
⢠Drive your sustainable digital transformation with focus on innovation and scale It was founded in 2004, and is headquartered in Chicago, Illinois, USA, with a workforce of 201-500 employees. Its website is http://sphereinc.com.
Company H1B Sponsorship
⢠Sphere has a track record of offering H1B sponsorships, with 3 in 2021, 1 in 2020. Please note that this does not guarantee sponsorship for this specific role.
Apply Now
Apply Now