Software Developer 4

At Oracle Health, we are redefining healthcare intelligence through cutting-edge AI and Search technologies. As a Principal Machine Learning Engineer, you will be responsible for designing and operationalizing scalable ML and LLM-powered systems that enhance clinical insights, streamline operations, and power intelligent search experiences across our products.

You will serve as a technical leader, mentoring engineers and data scientists, defining solution architectures, and ensuring end-to-end reliability and performance in ML and Search pipelines.

Design and implement scalable AI and LLM applications including RAG (Retrieval-Augmented Generation), embeddings, and multi-agent architectures for healthcare data and knowledge systems.

Architect and optimize enterprise Search solutions using OpenSearch (or Elasticsearch), including:

Designing and maintaining Universal Search Documents (USDs) with rich metadata, relevance signals, and domain-specific ranking.

Implementing efficient indexing pipelines and query optimization strategies for structured and unstructured healthcare data.

Tuning search relevance using clickstream and behavioral signals, boosting, and custom scoring.

Building semantic search layers using vector embeddings and hybrid retrieval (BM25 + ANN).

Collaborate with data, engineering, and product teams to integrate Search and ML pipelines seamlessly into production.

Establish and maintain search performance monitoring, relevance evaluation, and A/B experimentation frameworks.

Lead teams in developing responsible, explainable, and secure AI solutions that comply with healthcare data standards and regulations.

Mentor engineers and scientists, fostering technical excellence and innovation.

Contribute to architecture reviews, patents, and thought leadership in AI and Search innovation.

Master's or PhD in Computer Science, Data Science, or related technical field.

8+ years of experience in ML or AI engineering, with at least 2 years of hands-on experience in OpenSearch (or Elasticsearch).

Proven track record delivering end-to-end AI or search-based applications in production.

Strong proficiency in Python, PyTorch/TensorFlow, and cloud platforms (OCI, AWS, or Azure).

Deep understanding of LLMs, RAG pipelines, and embedding-based search.

Experience creating, maintaining, and optimizing Universal Search Documents (USDs)-including schema design, signals integration, and ranking models.

Strong command of query DSL, aggregation frameworks, and performance optimization for OpenSearch clusters (e.g., sharding, caching, and scaling strategies).

Experience integrating LLMs with OpenSearch for semantic and generative retrieval.

Familiarity with vector databases, hybrid retrieval systems, or cross-modal search.

Experience with data pipeline orchestration (Airflow, Prefect, or similar).

Experience leading cross-functional AI/ML programs or search relevance initiatives.

Knowledge of healthcare data systems, interoperability, and compliance frameworks (e.g., HIPAA, FHIR).

Contributions to open-source search or ML communities, or published research in AI/ML.

Career Level - IC4