Engineering

ML Engineer

On-siteFull-Time, ContractActive

About the role

Location: On-site. Work Type: Full Time, Contract. At Staff Outsourcing, we are committed to delivering innovative and cutting-edge technology solutions to our clients. We focus on leveraging AI and Machine Learning to build intelligent systems that drive efficiency and create data-driven insights. Join our dynamic team of professionals where your contributions directly impact businesses on their digital transformation journey.

Responsibilities

Deploy machine learning workloads, preferably in AWS using SageMaker
Implement MLOps practices including monitoring, alerting, CI/CD pipelines, Docker containerization, and testing
Work closely with data engineering and software teams to ensure seamless deployment of ML models into production
Ensure code quality and maintain version control using GitHub, following collaborative best practices
Leverage cloud-native services on AWS (S3, API Gateway, Lambda, ECS) or comparable platforms like MS Azure and Google Cloud
Collaborate with cross-functional teams to translate business requirements into actionable technical solutions

Requirements

Advanced proficiency in Python and strong knowledge of SQL
Hands-on experience deploying machine learning workloads in cloud environments, preferably AWS SageMaker
Practical experience implementing MLOps, including monitoring, alerting, CI/CD pipelines, Docker builds, and automated testing
Nice to Have: Proficiency with version control systems like GitHub, including familiarity with workflows and collaborative coding practices
Nice to Have: Experience working with AWS cloud-native services such as S3, API Gateway, Lambda, ECS or equivalent services on MS Azure or Google Cloud
Nice to Have: Strong communication skills in English, both written and verbal

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