Senior Applied AI Engineer

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Requirements:

• 5+ years of experience deploying AI models with demonstrated business impact.
• Proven track record of designing, deploying, and managing end-to-end AI solutions, with a particular emphasis on Generative AI.
• Deep Expertise in utilizing tools for Generative AI interaction (OpenAI, Bedrock, Huggingface TGI, Ollama, langchain, llamaindex).
• Expertise in machine learning tools (e.g., sklearn, PyTorch/TensorFlow, Hugging Face).
• General experience in cloud ML platforms (AWS, Azure, GCP), especially with their ML services (Sagemaker and Azure ML).
• Successful monitoring of model performance post-deployment, with an ability to link AI solutions to tangible business impacts.
• Strong capability for cross-team collaboration, working seamlessly with stakeholders across functional areas to deploy AI solutions that meet broader business needs.
• A natural problem-solver, comfortable with navigating ambiguity and making decisions in complex environments.
• A lifelong learner, continuously seeking to stay updated on new technologies and methodologies in the fast-evolving AI landscape.
• Familiarity with Agile methodologies, demonstrating effectiveness in a fast-paced, iterative development environment.
• Interest in the intersection of healthcare and AI.
• BA/BS in Computer Science or a related technical field or equivalent practical experience.

Responsibilities:

• Lead the creation of AI solutions specifically harnessing the power of LLMs. Play a pivotal role in influencing business outcomes by deploying new solutions, working closely with product and business collaborators.
• Work with industry-standard LLM APIs to inject cutting-edge AI functionalities into broader applications using your experience with cloud platforms like AWS and Azure.
• Create models that drive business outcomes and make iterative improvements based on data-driven insights. Ensure deployed models operate at peak efficiency, requiring a vigilant approach to performance monitoring and adjustment.
• Deploy models within an Agile development framework, showcasing flexibility, rapid iteration, and a commitment to constant improvement. Proactively collaborate within the Applied AI team and cross-functionally with other development teams, product and business stakeholders to iterate on ideas, solve problems, and achieve shared goals.