PLEASE NOTE BEFORE APPLYING:

CODOXO IS NOT ABLE TO OFFER SPONSORSHIP OR ACCOMMODATE ANY CANDIDATES THAT ARE CURRENTLY BEING SPONSORED NOW OR IN THE FUTURE

 

 

Of the $3.8T we spend on healthcare in the United States annually, about a third of it is estimated to be lost due to waste, fraud and abuse.  Codoxo is the premier provider of artificial intelligence-driven solutions and services that help healthcare companies and agencies proactively detect and reduce risks from fraud, waste, and abuse and ensure payment integrity. Codoxo helps clients manage costs across network management, clinical care, provider coding and billing, payment integrity, and special investigation units. Our software-as-a service applications are built on our proven Forensic AI Engine, which uses patented AI-based technology to identify problems and suspicious behavior far faster and earlier than traditional techniques.

 

We are venture backed by some of the top investors in the country, with strong financials, and remain one of the fastest growing healthcare AI companies in the industry. 

 

Position Summary:

The Senior Machine Learning AI Engineer will architect, build, and operate Codoxo’s next‑generation AutoML Platform — a foundational system that will power all future machine learning products, model lifecycles, and customer‑specific deployments. This is a rare opportunity for a top‑tier engineer to define how models are trained, optimized, deployed, and continuously improved across millions of healthcare claims, all within fully isolated single‑tenant AWS environments. The role also owns our Model‑as‑a‑Service (MaaS) framework, core MLOps pipelines, saving theme ML optimization framework, and automated retraining systems while working directly with Codoxo’s AI Prototyping, Product Integration, and Platform Engineering teams.

 

Key Responsibilities:

  • Lead the design and build-out of Codoxo’s AutoML Platform as a flagship engineering initiative — creating a scalable, automated, and customer‑isolated system for model training, feature engineering, hyperparameter optimization, and evaluation.
  • Architect Codoxo’s Model‑as‑a‑Service (MaaS) layer on AWS (SageMaker, Django, Batch,  ECS/EKS, API Gateway) to deploy secure, high‑performance inference endpoints across single‑tenant environments.
  • Develop production‑grade MLOps pipelines including CI/CD for ML, automated approvals, model lineage, auditability, and monitoring.
  • Implement automated retraining pipelines triggered by drift detection, new data arrival, or scheduled intervals.
  • Build observability for model health, drift, inference latency, cost efficiency, and cross‑customer performance using CloudWatch and Model Monitor.
  • Create reusable feature pipelines and experimentation environments to accelerate Data Science productivity.
  • Leverage our model performance and code utilization dashboards to automate model regeneration using Claude Code and seamlessly retire outdated models in favor of more relevant replacements.
  • Ensure all ML components meet Codoxo’s HITRUST, NIST 800‑53, and FedRAMP requirements.

 

Qualifications:

  • 5+ years building and operating ML or data platforms in production environments.
  • Expertise in AWS ML/AI stack: SageMaker, Lambda, Django, Batch, EMR, ECR, ECS/EKS, Step Functions, CloudWatch, EventBridge, S3.
  • Strong Python engineering skills for ML pipelines, infrastructure, and automation. Familiarity with LLM coding solution is a must (e.g. Claude Code, Cursor, Windsurf,  Google Gemini Code Assist, AWS Q Code Developer, etc.).
  • Experience designing AutoML systems, hyperparameter optimization workflows, or large‑scale training infrastructure.
  • Hands‑on experience with MLOps tooling such as MLflow, SageMaker Pipelines, or Kubeflow.
  • Deep understanding of secure architecture patterns in single‑tenant AWS environments (KMS, IAM, VPC isolation).
  • Previous experience in Data Science and LLM development.
  • GPU training or inference experience.
  • Model explainability, fairness, or responsible AI frameworks.
  • Terraform, CDK, or Pulumi experience.
  • FastAPI/Django/Flask experience for AI microservices.
  • Physical Requirements: Work is performed in an office environment (either in our office or work-from home) and requires the ability to work on a computer, operate standard office equipment, and work at a desk. 

 

 

Accessibility Notice: If you need reasonable accommodation for any part of the employment process due to a physical or mental disability, please send and email to careers@codoxo.com with the subject "Accommodation". Reasonable accommodation requests will be considered on a case-by-case basis.

 

Benefits for You

Health, Dental, and Vision insurance with 100% employee premium coverage (Starts Day 1)

Unlimited PTO

Annual Professional Development stipend

Annual home office stipend

401K Match (after 90 days)

 

We are an Equal Opportunity Employer:

Codoxo provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.  This policy applies to all terms and conditions of employment.