UpHill is the place where health professionals can find best practices to decide and train.
We're backed and trusted by top-tier investors and leading clients (e.g. Luz Saúde, Caixa Capital, Bynd, Maze, Brighteye Ventures, Novartis, Pfizer, etc).
We are seeking a talented Lead AI Engineer to join our dynamic team and contribute to the development of a groundbreaking decision support SaaS platform. As a Lead AI Engineer, you will play a pivotal role in designing, implementing, and productizing AI solutions that will drive innovation in healthcare.
Requirements:
M.Sc. with strong Computer Science and Statistical Learning components (e.g. Computer Science, Electrical Engineering, Physics, Aerospace Engineering, etc). Ph.D. is valued.
Minimum of 4 years of work experience in applied Machine Learning roles.
Extensive experience with Generative AI and Large Language Models (LLMs).
Proven track record of deploying Large Language Models in production environments.
Proficiency in Python or other commonly used languages in AI/ML development.
Hands-on experience with open-source frameworks like LangChain.
Experience leveraging a variety of services to act as data sources.
Proactivity and enjoyment in starting projects from scratch.
Capability to demonstrate and evaluate AI solutions via experimental methods, particularly through hands-on creation of prototypes.
Able to create end-to-end working prototypes - from planning, architecture, data engineering, analysis, and algorithm implementation.
Commitment to continuous learning and staying updated with advancements in the field of AI.
Flexibility and adaptability to thrive in a dynamic environment where projects and requirements may change frequently.
Experience with or knowledge of Agile Software Development methodologies.
Devotion to the project and ability to deliver under tight deadlines.
Responsibilities:
Lead projects to apply the latest AI technologies, enhancing the functionality of our applications.
Design, implement, and productize AI pipelines with a focus on seamless data handling, preprocessing, design engineering, deployment, and monitoring.
Architect end-to-end LLMOps solutions using cloud technologies, automation, and orchestration tools, ensuring scalability, reproducibility, and reliability of AI/ML solutions.
Develop Generative AI solutions and prompt management frameworks using cutting-edge methods to generate diverse and high-quality insights.
Collaborate cross-functionally with different teams to identify opportunities for improvement and innovation.
Work closely with the Engineering and Product team to understand business requirements, translate them into technical solutions, and enhance our products and data infrastructure.
Optimize AI algorithms and models for processing structured and unstructured data.
Stay updated with emerging trends in AI and technologies, applying new techniques and best practices to ongoing projects.
Ensure the quality and reliability of AI solutions through rigorous testing and validation.
Document AI models, algorithms, and systems for internal and external stakeholders.
#J-18808-Ljbffr