Lirio, the world leader in behavior change AI, unites behavioral science and artificial intelligence to deliver hyper-personalized communications that drive actions to better health. The company’s cloud-based solution leverages large volumes of patient health information combined with third-party data to compute unique behavioral models that learn to effectively engage people over time by understanding what activates them.
Who You Are:
You’re passionate about transforming people’s health through technology. You’re looking to be part of a dynamic organization that moves quickly, where you can learn and grow, and work alongside colleagues to develop and improve our solutions. You have a growth mindset who seeks progress over perfection.
What You'll Be Doing:
The Machine Learning (ML) Engineer will be responsible for designing, implementing and maintaining software for the machine learning workflow within Lirio’s Behavior Change AI Platform. This role will involve collaboration with Lirio researchers and other engineers to design, develop and deploy Lirio’s machine learning agent through
- Implementing prototypes and proofs-of-concept,
- Evaluating various approaches to improving agent performance,
- Incorporating the changes into the production agent codebase,
- Configuring production agents for each client, and
- Assisting as needed with performance analysis, troubleshooting and corrective/perfective maintenance.
This role will involve working closely with computer scientists, machine learning engineers and data engineers to design, develop, and maintain software components within Lirio’s machine learning workflows. Tasking for this position will include ML software design and development, client operations and maintenance support, and regular contributions to strategic and tactical discussions about the Lirio ML workflow and its research and engineering roadmaps. Additionally, this role will embrace Lirio’s culture of cross-team collaboration and agile development and will contribute to shaping our platform strategy. The role requires a software engineer with a deep understanding of machine learning and the drive and initiative to make an impact in other’s lives through systems that promote better health care engagement.
Design/Develop/Evaluate New ML Workflow Features (45%)
- Work as member of Lirio’s Behavioral Reinforcement Learning (BRL) Team, collaborating within that team and representing BRL in collaborating with other internal organizations.
- Design and develop ML software engineering solutions for implementation within Lirio’s AI Behavior Change Platform, including the various components of the ML workflow such as feature engineering, training pipeline, policy measurement and evaluation, ML agent design, and ML service architecture.
- Contribute to technical discussions and plans to improve the company’s overall software processes and practices, software quality, cadence and delivery lifecycle through automation and CI/CD pipelines using DevOps methodologies.
Configuration, Deployment and Maintenance of the ML Workflow (40%)
- Provide operations and maintenance software engineering support for fielded instances of Lirio’s AI Behavior Change Platform, including troubleshooting, testing, and corrective/perfective maintenance.
- Provide customer operations support for configuring new client instances of Lirio’s AI Behavior Change Platform
- Contribute to technical discussions and plans to improve/automate the processes and operations around its machine learning applications.
Contributing to ML Workflow Research and Prototypes (15%)
- Propose and test new approaches to machine learning problems
- Assist the research staff in pathfinding new ways to improve Lirio’s ML Agent and overall ML workflow
- Implement and evaluate prototypes using the Lirio Experimental Framework
- Bachelor’s degree (Master’s preferred) in Computer Science, Engineering, Mathematics, or a related field.
- Candidates with academic research experience are preferred. Strong candidates with publications in top ML/AI conferences such as NeurIPS, ICML, KDD, AAAI, etc are highly preferred.
- Deep knowledge of machine learning concepts and their application, including traditional approaches to both supervised and unsupervised learning as well as advanced topic such as deep learning networks and reinforcement learning.
- Ability to fluently discuss and describe technical details of machine learning algorithms with experts and lay people
- Ability to develop and implement novel approaches to machine learning
- Ability to process and manipulate structured and unstructured data before ML modeling.
- 2-3 years experience developing with data science/machine learning software tools using python, such as pandas, numpy, Tensorflow, R, or PyTorch.
- Experience with database technologies, data warehousing, and hands-on experience writing SQL queries.
- Experience using build tools with continuous integration or continuous delivery.
- Strong understanding of the agile software development process.
- Experience with cloud service technologies, specifically AWS.