Lead AI Research Engineer

Role Overview

• By embodying our core purpose of customer obsession, new ideas, and driving innovation, and delivering excellence, you will help ensure that every touchpoint is meaningful and contributes to our mission of redefining the possible in healthcare.
• The Senior Engineer, AI is responsible for building AI and Machine learning models and pipelines, with a focus on generative AI, LLMs and predictive modelling.
• The successful candidate will work closely with data scientists and product leads to implement AI models, build required data and code pipelines through rigorous engineering disciplines.
• Coordinate between Data Scientists and Product Analysts.
• Automate infrastructure used by the Data Science team.
• Design, develop, and deploy advanced AI models and algorithms to solve complex business problems.
• Test and deploy models.
• Develop minimum viable products based on machine learning.
• Automate processes by utilizing machine learning.
• Lead AI projects from conception to implementation, ensuring timely delivery and high-quality outcomes.
• Ability to create AI models utilizing deep learning, neural networks, and ML algorithms to derive business insights and fuel informed decision-making.
• Advanced experience in programming, software engineering, and data science fields.
• Mentor and coach junior associates on the team.
• Ability to utilize various tools and methods to process data as well as create and keep up AI systems.
• Communicate findings and recommendations to stakeholders through clear and compelling data visualizations and presentations.

Requirements

• 5+ years of practical experience as an engineer with focus on implementation of AI / ML machine learning solutions.
• Masters in Computer Science / Machine Learning / AI, or related work experience with the design, building and evaluation of Machine Learning systems.
• 3+ years’ experience with Machine Learning ecosystem tools, including pytorch/tensorflow, scikit-learn, xgboost or equivalents.
• Advanced knowledge of MLOps fundamentals, including orchestration tools, cloud compute, and observability tools.
• Advanced understanding of cloud platforms e.g. Azure / GCP / AWS and their AI tool set.
• Practical experience working with data and code pipelines.
• Ability to work independently with limited supervision.
• Ability to implement, test and deploy Machine Learning models.
• Advanced experience with langchain / llamaindex / haystack / Azure AI studio, vector databases and retrieval techniques, or equivalent common tools in the emerging LLM-enable tech stack is a plus.
• Skilled in accessing and handling databases via SQL, Azure Data Factory or similar.
• Alternatively, familiarity with data storage/management systems or Big Data framework (like Hadoop, Spark) expected to be known or used.
• Advanced knowledge in Software Development best practices such as Continuous Integration, Unit/Integration Testing, Code Reviews.
• Excellent communication skills, both written and verbal.
• Knowledge of Revenue Cycle Management, Collections, or financial industries is desirable but not necessary.

Tech Stack

• AWS
• Azure
• Cloud
• Google Cloud Platform
• Hadoop
• PyTorch
• Scikit-Learn
• Spark
• SQL
• Tensorflow

Benefits

• Associate Benefits – We offer a comprehensive benefits package designed to support the physical, emotional, and financial health of you and your family, including healthcare, time off, retirement, and well-being programs.
• Our Culture – Ensemble is a place where associates can do their best work and be their best selves. We put people first, last and always.
• Growth – We invest in your professional development. Each associate will earn a professional certification relevant to their field and can obtain tuition reimbursement.
• Recognition – We offer quarterly and annual incentive programs for all employees who go beyond and keep raising the bar for themselves and the company.