AI Engineer

Role Overview

Apply your machine learning expertise to help train next-generation AI systems through high-quality, real-world input that improves how models learn, reason, and perform. Prior AI experience is not required, and relevant domain expertise is valued.

Key Responsibilities

• Design, build, and optimize robust machine learning models for production environments.
• Implement and automate end-to-end ML pipelines using CI/CD practices.
• Use AWS services to build scalable AI infrastructure and deploy models.
• Orchestrate containerized workloads with Kubernetes to support high availability and scalability.
• Partner with data scientists, engineers, and researchers to turn complex business problems into actionable ML solutions.
• Evaluate, preprocess, and frame real-world data problems for effective machine learning applications.
• Clearly document and communicate findings, technical decisions, and solution approaches.

Qualifications

• Demonstrated expertise in machine learning algorithms, model development, and deployment.
• Strong Python or Java programming skills and experience with large-scale software engineering projects.
• In-depth experience with CI/CD workflows and automation tools.
• Hands-on experience using AWS cloud services for machine learning applications and data pipelines.
• Advanced Kubernetes knowledge for orchestrating containerized ML workloads.
• Excellent written and verbal communication skills, including clear technical documentation and collaborative teamwork.
• Ability to scope, structure, and solve complex real-world data challenges.

Preferred Qualifications

• Familiarity with deep learning frameworks such as TensorFlow or PyTorch.
• Experience in high-growth or startup environments.
• A strong publication record or contributions to open-source AI projects.

Work Terms

• Remote contract engagement.

Compensation

• $30 to $90 per hour.