About this role
Role Overview
Apply machine learning and engineering expertise to help train next-generation AI systems through high-quality, real-world technical input. Your work will help improve how models learn, reason, and perform. Prior AI experience is not required, though the technical capabilities below are essential for this role.
Key Responsibilities
- Design, build, and optimize production-ready machine learning models.
- 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 ML workloads with Kubernetes to support high availability and scalability.
- Partner with data scientists, engineers, and researchers to turn complex business problems into practical ML solutions.
- Evaluate, preprocess, and frame real-world data problems for machine learning applications.
- Clearly document and communicate findings, solution approaches, and technical decisions.
Qualifications
- Demonstrated expertise in machine learning algorithms, model development, and deployment.
- Strong programming skills, ideally in Python or Java, including experience on large-scale software engineering projects.
- In-depth experience with CI/CD workflows and automation tools.
- Hands-on experience using AWS cloud services for ML applications and data pipelines.
- Advanced Kubernetes knowledge for containerized ML workloads.
- Excellent written and verbal communication skills, including technical documentation and team collaboration.
- Ability to scope, structure, and solve complex real-world data challenges.
Preferred Qualifications
- Familiarity with TensorFlow, PyTorch, or similar deep learning frameworks.
- Experience in high-growth or startup environments.
- A strong publication record or open-source AI project contributions.
Work Terms
- Remote contract engagement.
Compensation
- $30 to $90 per hour.