About the role
Position: AI Engineer
Type: Contract
Compensation: $30 - $90/hour
Location: Remote
Commitment: 10-40 hrs/week
Role Responsibilities
Design, build, and optimize robust machine learning models for production environments. Implement and automate end-to-end ML pipelines using CI/CD best practices. Leverage AWS services for scalable AI infrastructure and model deployment. Orchestrate containerized workloads using Kubernetes to ensure high availability and seamless scalability. Collaborate with data scientists, engineers, and researchers to translate complex business problems into actionable ML solutions. Evaluate, preprocess, and frame real-world data problems for effective machine learning applications. Document and communicate findings, solution approaches, and technical decisions with clarity and precision.
Requirements
Proven expertise in machine learning algorithms, model development, and deployment. Strong programming skills, ideally in Python or Java, with experience in large-scale software engineering projects. In-depth experience with CI/CD workflows and automation tools. Hands-on expertise with AWS cloud services for ML applications and data pipelines. Advanced knowledge of Kubernetes for orchestrating containerized ML workloads. Exceptional written and verbal communication skills, with a focus on clear technical documentation and team collaboration. Demonstrated ability to scope, structure, and solve complex, real-world data challenges.
Application Process
Easy Apply on LinkedIn Check email for next steps Participate in resume evaluation & interview stage
About Crossing Hurdles
Similar Jobs
About the role
Position: AI Engineer
Type: Contract
Compensation: $30 - $90/hour
Location: Remote
Commitment: 10-40 hrs/week
Role Responsibilities
Design, build, and optimize robust machine learning models for production environments. Implement and automate end-to-end ML pipelines using CI/CD best practices. Leverage AWS services for scalable AI infrastructure and model deployment. Orchestrate containerized workloads using Kubernetes to ensure high availability and seamless scalability. Collaborate with data scientists, engineers, and researchers to translate complex business problems into actionable ML solutions. Evaluate, preprocess, and frame real-world data problems for effective machine learning applications. Document and communicate findings, solution approaches, and technical decisions with clarity and precision.
Requirements
Proven expertise in machine learning algorithms, model development, and deployment. Strong programming skills, ideally in Python or Java, with experience in large-scale software engineering projects. In-depth experience with CI/CD workflows and automation tools. Hands-on expertise with AWS cloud services for ML applications and data pipelines. Advanced knowledge of Kubernetes for orchestrating containerized ML workloads. Exceptional written and verbal communication skills, with a focus on clear technical documentation and team collaboration. Demonstrated ability to scope, structure, and solve complex, real-world data challenges.
Application Process
Easy Apply on LinkedIn Check email for next steps Participate in resume evaluation & interview stage