CareMessage is hiringSenior AI/ML Engineer
Join us to Improve Health Equity for 5 Million People!
CareMessage is the technology non-profit building the largest patient engagement platform for low-income populations in the United States. Powered by the Health Equity Engine™, the platform enables organizations to combine messaging, data, and interoperability to increase access to care, improve clinical outcomes, and address social drivers of health.
With 20 million patients reached since 2013, CareMessage is the only patient engagement solution proven to improve health equity at scale. The team, many with lived experiences in these communities, leverages a nonprofit model to reinvest revenue into impact. CareMessage is the partner of choice for organizations committed to advancing health equity.
CareMessage is seeking a talented and experienced Senior (L3) AI/ML Engineer to join our dynamic data team. As an AI/ML Engineer specializing in healthcare, you will have the opportunity to work on cutting-edge projects that leverage artificial intelligence and machine learning in the areas of clinical outcomes, increased access to care, and improvements in Social Determinants of Health for people from low-socio-economic backgrounds.
As an AI/ML Engineer at CareMessage, you will play a crucial role designing, building, and deploying machine learning models and AI-powered systems that help drive better decision-making across our platform. As a key strategic investment for the company and product, you will be working on highly impactful and visible outcomes similar to the AI Assistant we recently released. This is an opportunity to be at the forefront of spurring insight and innovation through the use of machine learning, artificial intelligence, and data to drive strategic impact and decision making throughout CareMessage. One of the goals of this team is to leverage machine learning and AI to analyze patient interactions with CareMessage, enabling us to extract actionable insights and build intelligent systems that will drive measurable and scalable improvements for the populations we support.
You will work closely with a multidisciplinary, agile team to identify key problems, design AI/ML solutions, preprocess and clean data, build and test machine learning models, interpret results, and deploy models into production. These solutions will harness the organization’s connected data, enabling intelligent, data-driven decision-making and automated actions. This is an exceptional opportunity for someone with a passion for machine learning and AI, and a desire to make a significant social impact.
If you share our mission-driven commitment to advancing health equity for individuals of low socio-economic status nationwide and have a strong understanding of machine learning algorithms, data processing, along with a passion for using technology to improve healthcare outcomes, we would love to hear from you.
Note: Due to the nature of this role we are only accepting US-based candidates. At this time, we are not able to sponsor work visas. Applicants must be authorized to work in the United States on a full-time basis without sponsorship.
Requirements
- 5+ years as an AI/ML Engineer with a focus on healthcare AI/ML use cases.
- 5+ years of experience with Python and machine learning frameworks such as scikit-learn, SparkML, TensorFlow, PyTorch, pandas, Hugging Face, etc.
- Strong understanding of machine learning algorithms (e.g., supervised and unsupervised learning, natural language processing, reinforcement learning).
- Proven track record of applying ML techniques to healthcare data, particularly with natural language processing (NLP), Generative AI, and large language models (LLMs).
- Hands-on experience in training, tuning, and deploying models in production environments, including proficiency in advanced prompting techniques and fine-tuning LLMs for various use cases.
- Hands-on experience deploying machine learning models in cloud environments (preferably GCP, but AWS or Azure are acceptable).Expertise in building and scaling end-to-end machine learning pipelines in production environments.
- Familiarity with MLOps practices for model management and deployment.
- Excellent communication skills to convey complex technical concepts to non-technical stakeholders and to collaborate effectively within a cross-functional team.
- Strong expertise in data preprocessing, feature engineering, and model evaluation techniques.
- Ability to translate business requirements and metrics into machine learning model specifications and solutions.
- Experience working in distributed systems-based architectures, developing APIs, and implementing/deploying scalable backend services.
- Hands-on experience in data engineering, orchestration, ETL, and distributed unstructured data processing.
- Experience with cloud infrastructure, including Docker/Kubernetes deployments, security, and cost optimization.
- Knowledge of healthcare standards such as HL7, FHIR, or HIPAA compliance.
Nice to Have:
Job Responsibilities
- Collaborate with engineers to develop, modify, and optimize machine learning models, including both generative AI (LLMs) and discriminative AI models, tailored to address specific business challenges.
- Leverage large language models (LLMs) for applications such as text generation, text classification, and other AI-powered solutions.
- Design and implement models for predictive analytics and classification tasks, ensuring high accuracy and reliability.
- Design scalable, production-ready AI/ML solutions, taking models from initial concept through to deployment.
- Monitor and maintain models post-deployment, making necessary adjustments to improve performance and address changing requirements.
- Conduct experiments and fine-tune machine learning models to optimize their accuracy and overall performance.
- Create high-level and detailed design plans for AI/ML production solutions, including selecting appropriate algorithms, data sources, infrastructure, and technologies that align with the organization's goals and constraints
- Design and implement scalable AI/ML pipelines that can efficiently handle production-level data and adapt to various use cases.
- Ensure successful deployment of models into production environments, focusing on stability, reliability, and seamless integration.
- Continuously track the performance of AI/ML solutions in production, addressing any issues, identifying model drift, and making necessary optimizations.
- Manage and automate model evaluation, training, and deployment processes using cloud infrastructure, with a focus on GCP (experience with AWS or Azure is also acceptable).
- Fine-tune machine learning models to maximize performance and scalability, ensuring they meet diverse and evolving user needs.
- Understand both company and customer challenges, leveraging AI capabilities to develop innovative solutions that address these problems.
- Ensure the development and deployment of scalable, efficient, and high-quality AI solutions that meet business needs.
- Participate in design, architecture, and code reviews. Foster collaboration within the team, ensuring high-quality code standards are maintained while guiding the team through technical challenges and roadmap deliverables.
- Design and build efficient, resilient machine learning platforms and software products capable of scaling to meet production demands.
- Adhere to best practices for data privacy and security, ensuring full compliance when working with sensitive data.
- Actively seek opportunities to enhance and upgrade AI/ML infrastructure, tools, and solutions.
- Improve best practices for machine learning engineering by producing high-quality code, documentation, automated tests, and precise monitoring systems.
Model Design & Development:
Infrastructure, Scaling & Deployment:
Problem-Solving & Business Impact:
Technical Expertise & Architecture:
Within 1 Month You'll:
- Gain a foundational understanding of our product, customers and patients
- Meet key internal stakeholders and begin to understand policies and protocols
- Establish rapport with existing Engineers across various product teams
- Build out basic understanding of existing AI applications within CareMessage
Within 3 Month You'll:
- Gain a strong understanding of our technical environment and identify areas for growth in our processes, systems and/or tooling for AI/ML development
- Reviewed existing usage of AI, improved monitoring/performance capabilities, and suggested optimizations to the model.
- Identified, documented, and received approval for a proposed technical solution for use case in conjunction with the product team for the application of AI/ML.
Within 6 Month You'll:
- Have a deep understanding of the product platform, our AI/ML needs and work in conjunction with management to refine the plan to meet our long term AI/ML goals.
- Have defined and chosen the appropriate tools and frameworks to support ML/AI model building, training, and deployment.
- Have developed an initial model to solve for the use case identified in the first 3 months.
$189,500 - $189,500 a year
Compensation Details:
This role is currently set at a L3 AI/ML Engineer level, equivalent to someone who has held two or more AI/ML Engineering roles with related experience for multiple years and is extremely proficient in their craft.
Our salary allocation for this role is $189,500.
Note: If you don’t fit this description perfectly (in particular, if you come from an under-represented group) but have held a Data Science role in the past, please apply!
We believe in equal work for equal pay. All team members performing the same role at the same level are paid the same regardless of where they are in the world.
Working at CareMessage
We take care of our employees by offering competitive salaries and benefits packages. We ensure our team feels cared for so that we, in turn, can help support our safety net organizations and underserved populations.
We compensate fairly and equitably
Flexible work hours; fully remote team
We believe in equal work for equal pay: all team members performing the same role at the same level are paid similarly, regardless of where they are in the world
Paid parental leave for biological and adopted children
We give you time off to thrive
Half-day Fridays, every Friday
18 paid company holidays, including a one week mid-year and one week end-of-year break
9 wellness days to be used for self-care- or anything that comes up in life
15 days of PTO
1-month (20 working days) paid sabbatical after the 4-year anniversary, and every 4 years thereafter
We support your health, wellness, and growth
Generous medical, dental, and vision insurance for employees and their families
Health Savings Accounts and Flexible Spending Accounts
401k retirement plan
Short & long-term disability insurance
$100 per employee yearly wellness budget, with flexibility to spend on physical, emotional, and mental wellness resources
PerkSpot: Instant access to discounts on products & services from hundreds of vendors
Annual budget for professional and personal development (webinars, online courses, books, and more)
Volunteerism incorporated in onboarding and encouraged on an ongoing basis
Something went wrong.