Temporary AI & Machine Learning Engineer - jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Temporary AI & Machine Learning Engineer based in United States.

This role offers the opportunity to build advanced AI solutions that address complex business challenges across healthcare analytics, insurance, and data-driven decision-making. The ideal candidate will combine machine learning expertise, software engineering skills, and AI innovation capabilities to develop production-ready systems. You will collaborate with multidisciplinary teams including data scientists, actuaries, engineers, and business experts to transform ideas into scalable AI applications. This position is designed for a hands-on technical professional who enjoys experimenting with emerging technologies while delivering measurable business impact. You will contribute to predictive modeling, large language model applications, agentic workflows, and AI-enabled automation initiatives. The role provides flexibility through a remote work environment and the opportunity to influence how modern AI capabilities are adopted across an organization.

Accountabilities:

The AI & Machine Learning Engineer will design, develop, and deploy innovative AI solutions while helping teams leverage emerging technologies effectively. This temporary role requires strong technical ownership, creativity, and the ability to translate advanced AI concepts into practical business applications.

• Design, architect, test, and deploy production-grade AI and machine learning solutions for high-impact business use cases.
• Build reusable data pipelines, modeling infrastructure, and AI frameworks that enable faster development and deployment of predictive solutions.
• Develop agentic AI workflows that automate established modeling processes and extend analytical capabilities to new prediction challenges.
• Create applications powered by large language models, retrieval-augmented generation (RAG) systems, and AI agents.
• Evaluate AI technologies, foundation models, and tools to identify the best solutions while considering security, reliability, performance, and cost requirements.
• Develop AI services and APIs that integrate with existing software products and operational workflows.
• Establish strong software engineering practices for AI systems, including scalability, testing, maintainability, and deployment automation.
• Prototype emerging AI concepts and transform successful experiments into production-ready capabilities.
• Identify opportunities where AI can improve healthcare analytics, software development, operational efficiency, and internal productivity.
• Support AI adoption by providing technical guidance, demonstrations, documentation, and mentorship to teams.

Requirements: