Join an agile AI Innovation Acceleration team that operates with startup speed to build cutting-edge AI use cases addressing critical business needs. The team's mission is to showcase AI's transformative power, deliver impactful solutions rapidly, and ensure seamless knowledge transfer to business and engineering teams.

This hands-on engineering role is essential for advancing AI adoption and fostering a culture of innovation. As an AI Innovation Acceleration Specialist, you will identify, develop, and deploy end-to-end AI/ML solutions that deliver tangible business value. You'll thrive in a fast-paced environment, translating complex challenges into actionable AI architectures and technical specifications, then implementing and delivering these systems.

- Lead end-to-end AI/ML model and application development, from ideation and data exploration to rapid prototyping and initial deployment. - Partner closely with business and engineering teams to understand challenges, identify AI use cases, and translate requirements into technical specifications and solution architectures. - Architect, implement, and deliver scalable, robust AI solutions, ensuring seamless integration with existing systems. - Facilitate knowledge transfer through documentation, training, mentorship, and pair-programming. - Stay current with AI/ML advancements, evaluating and recommending new tools and best practices.

A Bachelor's or Master's degree in Computer Science, Data Science, or a related quantitative field is required. Candidates should possess 5+ years of hands-on experience in AI/ML development with a proven track record of delivering end-to-end AI solutions.

Demonstrated experience building and deploying end-to-end AI applications, particularly those utilizing LLMs and associated frameworks, is crucial. This includes expertise in prompt engineering, fine-tuning, Retrieval Augmented Generation (RAG), and agentic frameworks.

Proficiency in Python and AI/ML frameworks like TensorFlow and PyTorch is essential. You must be adept at translating complex business needs into technical designs and implementing robust systems. Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices is also necessary.

Excellent communication skills are needed to articulate technical concepts to diverse stakeholders. Strong collaboration, interpersonal skills, and a passion for mentoring are highly valued. The ability to lead or significantly contribute to cross-functional projects is a key requirement.