AI/ML Engineer - Remote Work

Company: Torentify

Location: Location not specified (Remote)

Type: Full-time

Remote: Yes

Posted: 2026-10-31

About this role

About the Company

Commence delivers data-driven solutions, technology, and clinical expertise to support better healthcare outcomes and more efficient healthcare processes. The company focuses on human-centered, healthcare-relevant, and value-based solutions that use data to improve care delivery and program performance.

About the Role

Commence is seeking an AI/ML Engineer to build, train, and validate machine learning models that support clinical and operational data products across the healthcare ecosystem. The role also involves contributing to the production deployment of models, supporting document processing pipelines, and developing AI/LLM-driven workflows.

The successful candidate will independently manage defined model development tasks while collaborating with senior engineers on broader system design, architecture, and compliance requirements.

Key Responsibilities

  • Build, train, and validate machine learning models, including data ingestion, feature engineering, and model evaluation, based on requirements established by Senior Engineers or Data Scientists.
  • Contribute to deploying machine learning and AI models into production through APIs, batch processing, and streaming workflows under the direction of Senior AI/ML Engineers.
  • Support AI/LLM-driven workflows for document extraction, classification, and summarization using established frameworks and orchestration patterns.
  • Assist in implementing Retrieval-Augmented Generation (RAG) components, embedding strategies, and vector-based retrieval within architectures designed by senior engineers.
  • Apply established MLOps practices, including CI/CD pipelines, model versioning, and retraining workflows.
  • Use Databricks tools, including Workflows, Delta Lake, and Unity Catalog, and AWS services such as S3, Lambda, and Bedrock for model training and inference.
  • Monitor deployed model performance, including latency, throughput, and accuracy drift, and troubleshoot issues while escalating ...

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