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Salary: USD 195,000 - 255,000 / annual
Candid Health is transforming healthcare revenue cycle management (RCM) through intelligent automation. The company is building a cutting-edge platform to simplify billing, enhance claims processing, and eliminate administrative waste in healthcare systems.
As a Senior AI/ML Engineer, you will be a hands-on builder responsible for translating prototypes into differentiated, high-impact ML/AI use cases across the platform and customer base. You'll own outcomes by applying AI to real problems in medical billing, directly influencing both internal teams and external customers.
Key responsibilities:
- Identify and drive opportunities for when, where, and which AI/ML techniques deliver business value. Research industry best practices and leverage state-of-the-art technologies to design systems that support meaningful outcomes.
- Take compelling initial prototypes and ensure a strong foundation to scale and deploy them across the customer base.
- Partner with leadership and cross-functional teams to automate and scale products and workflows with high technical complexity, such as claim submission, resubmission, and workflow optimization. Drive Candid's AI roadmap and influence the product roadmap to enable customers to optimize RCM operations at scale.
- Architect infrastructure that leverages AI across every facet of the product. Structure and format data to support AI development. Establish rigorous processes for model training, testing, and monitoring—ensuring scalability, extensibility, and high security standards.
You are a tastemaker and strong hands-on builder who can navigate the complexities of medical billing and leverage technical expertise to deliver strategic AI- and ML-based solutions with impactful business outcomes. You have a customer-first and learner's mindset, value teaching others, and excel at explaining complicated ideas in simple terms.
Requirements:
- Bachelor's or Master's degree in Computer Science, Computer Engineering, Math, or similar field.
- 8+ years of experience building software of significant scale and complexity.
- 5+ years of AI engineering experience in a professional setting, preferably applying it to real-world solutions.
- Experience building systems that leverage ML technologies (e.g., built or used specific NLP models); knowledge of relevant tools, frameworks, and libraries.
- Understanding of the pros, cons, and tradeoffs of leveraging various AI solutions across use cases; ability to help make informed decisions around when to use deterministic (ML) vs. non-deterministic (LLM) approaches.
- Knowledge of right architecture and patterns to build systems of enduring value and scale.
- Clear and concise communication skills; ability to explain complicated ideas in simple terms both in-person and in writing.
- Experience with Google Cloud Platform, BigQuery, PostgreSQL, Metabase, Terraform, and Python is a plus but not required.
