AI ML Integration Engineer

Shearwater Health is a leading provider of healthcare staffing and technology solutions. Our mission is to empower healthcare professionals to deliver exceptional patient care. With a focus on innovation and collaboration, we are transforming the way healthcare services are delivered.

About The Role

We are seeking AI ML/Integration Engineer to join our growing team at Shearwater Health. This is a full-time, hybrid setup. Join our team to build, deploy, and integrate AI/ML solutions into enterprise applications. You'll work with Data Science, Engineering, and DevOps teams to deliver secure, scalable, and reliable AI-powered products.

Hybrid work setup

HMO on Day 1 with 2 Dependents upon regularization.

Group Life Insurance

Highly Competitive Salary

Annual Salary Increase and Performance Bonus

Service Incentive Leave (SIL) with Leave Conversion

Work-Life Integration

Key Responsibilities

Deploy and integrate AI/ML solutions into enterprise applications.

Develop APIs, microservices, and automated MLOps pipelines.

Manage cloud-based AI deployments (AWS, Azure, GCP).

Monitor, optimize, and troubleshoot production AI systems.

Ensure security, compliance, and governance standards.

Implement advanced AI technologies, including Generative AI and LLMs.

Maintain technical documentation and deployment best practices.

Qualifications

Bachelor's degree in Computer Science, IT, AI, Engineering, or related field.

3-8 years of experience in software development, ML engineering, or AI integration.

Must be knowledgeable with TensorFlow, PyTorch, or Scikit-learn.

Healthcare industry experience is a plus.

Preferred Skills

Experience deploying AI/ML and Generative AI solutions.

Knowledge of Agile/Scrum methodologies.

Tools: Git, Azure DevOps, Jenkins, Kafka, RabbitMQ, Prometheus, Grafana, Power BI, Tableau, Jira, and Confluence.

Experience with APIs (REST, GraphQL, gRPC), Docker, Kubernetes, and CI/CD tools.

Experience with AWS, Azure, or Google Cloud.

Familiarity with SQL and NoSQL databases.