Sr. AI & Data Scientist

Alignment Healthcare USA, LLC; Orange (CA); Sur place; USD 172 000 - 259 000; Plein temps

Résumé du poste

Alignment Healthcare USA, LLC seeks an experienced AI/ML leader to architect and deliver production-grade machine learning systems powering our clinical intelligence platform.

You will own the full lifecycle from research to deployment, collaborate across engineering, product, and clinical leadership, and mentor the data science organization to raise the bar on technical excellence.

Qualifications

• 5-8 years delivering production-grade data science or ML solutions with business impact.
• Track record architecting complex ML systems from research through production deployment.
• Strong software engineering foundations across multiple ML domains.
• Leadership experience spanning technical projects and mentoring data scientists.
• Continuous learning across ML/AI, healthcare analytics, and software engineering practices.
• Expert proficiency in data science methods, workflows, and best practices.

Responsabilités

• Architect end-to-end AI/ML systems for high-stakes healthcare applications and real-time engines.
• Own the full machine learning lifecycle from experimentation to production and monitoring.
• Establish instrumentation, observability, and feedback loops for production reliability.
• Drive technical excellence by applying state-of-the-art methods across DL, NLP/LLMs, CV, and causal inference.
• Partner with Product, Clinical, Operations, and Compliance to identify AI opportunities and communicate tech concepts to executives.
• Mentor team members through code reviews, architecture discussions, and hiring interviews.

Connaissances

Production ML experience

ML lifecycle management

Observability & instrumentation

Leadership & mentoring

Python/Java/SQL/PySpark

MLOps

Formation

PhD in Computer Science / ML / Statistics

Outils

Databricks

MLflow

Unity Catalog

Git

CI/CD

Docker

Description du poste

At Alignment Healthcare USA, LLC, this role focuses on building AI and data science solutions that power the company’s proprietary clinical intelligence platform. You will architect and deliver production-grade machine learning systems for complex healthcare use cases, moving from research and experimentation through reliable deployment. The work includes collaboration across engineering, product, and clinical leadership, along with mentoring responsibilities within the data science organization.

What you’ll do

• Architect end-to-end AI/ML systems for high-stakes healthcare applications, including risk stratification, clinical decision support, autonomous chart review, and fraud detection. Define technical approach, model selection, and system architecture for multi-model systems and real-time decision engines handling millions of healthcare transactions.
• Own the full machine learning lifecycle, from experimentation through production. Build scalable AI services covering experimentation, validation, deployment, monitoring, drift detection, and continuous improvement.
• Establish instrumentation and reliability practices by implementing observability, alerting, and feedback loops to support model performance and operational confidence in production environments.
• Drive technical excellence and innovation by researching and applying state-of-the-art methods across deep learning, NLP/LLMs, computer vision, and causal inference. Promote engineering best practices including code quality, testing, documentation, reusability, and maintainability.
• Partner with cross-functional leaders across Product, Clinical, Operations, and Compliance to identify high-value AI opportunities aligned with business strategy. Communicate technical concepts clearly for executive audiences and contribute to product roadmap and technology decisions.
• Mentor and raise the bar through code reviews, architectural discussions, and pair programming. Share knowledge via internal presentations and documentation, and support hiring by running technical interviews and reinforcing analytical rigor and modeling best practices.

Minimum qualifications

• 5-8 years delivering production-grade data science or ML solutions with demonstrated business impact.
• Track record architecting complex ML systems from research through production deployment.
• Strong software engineering foundations and expertise across multiple ML domains.
• Leadership experience spanning technical projects and mentoring data scientists.
• PhD in Computer Science, Machine Learning, Statistics, or a related field.
• Continuous learning across ML/AI advancements, healthcare analytics, and software engineering practices.
• Expert proficiency in data science methods, workflows, and best practices.

Technical strengths

• Advanced machine learning, including ensemble methods, deep learning, NLP/LLMs, and computer vision.
• Strong statistical analysis and experimental design capabilities.
• Expert programming skills in Python, Java, SQL, or PySpark, focused on production-grade, maintainable code.
• Advanced SQL experience with high-volume, high-dimensional healthcare data.
• Experience with Databricks (Spark, Delta Lake), MLflow, and Unity Catalog, plus cloud platform experience.
• Working knowledge of Git, CI/CD pipelines, Docker, and modern MLOps practices.
• Deep understanding of healthcare data (claims, clinical, member) and Medicare Advantage operations.
• Strong communication skills to translate technical complexity into business value for diverse stakeholders.
• Data visualization and storytelling capabilities with a demonstrated ability to influence technical decisions.

Technologies

• Python, Java, SQL, PySpark
• Databricks, Spark, Delta Lake, MLflow, Unity Catalog
• Git, CI/CD pipelines, Docker, MLOps
• NLP, LLMs, computer vision, ensemble methods, deep learning, causal inference, OCR, NER, entity extraction
• NoSQL databases, distributed computing, streaming architectures
• Cloud platforms: Azure, AWS, GCP

Preferred experience

• Healthcare domain expertise, especially Medicare Advantage, risk adjustment, or claims analytics.
• Experience with production document understanding systems (OCR, NER, entity extraction, LLM pipelines).
• Published research, open-source contributions, or patents in ML/AI.
• Ability to translate research innovations into production systems.
• Training or certification in MLOps, cloud platforms (Azure, AWS, GCP), or healthcare regulations (HIPAA, CMS).
• Experience with NoSQL databases, performance optimization, and distributed computing.
• Experience with real-time ML inference and streaming architectures.
• Contributions to internal ML platforms, frameworks, or open-source projects.
• Experience presenting at technical conferences or publishing research.
• Industry certifications in ML, cloud platforms, or healthcare analytics.

Physical requirements

• Regularly required to talk or hear.
• Regularly required to stand, walk, sit, use hand to finger, handle or feel objects, tools, or controls, and reach with hands and arms.
• Frequently lifts and/or moves up to 10 pounds.
• Specific vision abilities required, including close vision and the ability to adjust focus.

Location: Orange, CA (onsite)

Pay range: USD 172,364 - 258,547 per yearly. Pay range may be based on market location, education, responsibilities, experience, and other factors.

Licensure: Required: none.