Experity
From Experity's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
Position Overview We are looking for a Machine Learning Engineer to join Experity’s Data & AI team.
Position Overview
We are looking for a Machine Learning Engineer to join Experity’s Data & AI team. In this role, you will build, deploy, and optimize production-grade machine learning and Generative AI solutions that power our healthcare products. You will Design, Develop and Deploy scalable ML systems and work closely with Data Scientists, Software Engineers, Product Managers, and Platform teams to deliver meaningful outcomes for healthcare providers and patients.
Design, develop, and deploy machine learning models and AI services that power Experity’s Intelligent healthcare products.
Design and implement automated data collection, feature engineering, model training, evaluation, deployment, and monitoring ML pipelines to enable predictive analytics, recommendations, forecasting, classification, and automation.
Develop APIs and production services using Python and FastAPI. • Build and operationalize Generative AI solutions, including RAG pipelines and AI powered assistants.
Work with large-scale healthcare datasets and cloud-native data platforms.
Implement MLOps best practices for model training, deployment, monitoring, and governance.
Collaborate with cross-functional teams to translate business problems into AI driven solutions.
Contribute to architecture, technical design, and engineering best practices. Qualifications Required
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, AI, or a related field.
3+ years of experience building and deploying machine learning solutions in production environments.
Strong programming skills in Python and SQL.
Experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
Experience building APIs using FastAPI or similar frameworks.
Hands-on experience with Snowflake and modern data platforms.
Experience with AWS services such as SageMaker, S3, Lambda, RDS, DynamoDB, ECS/EKS, and API Gateway.
Experience with Docker, Kubernetes, CI/CD pipelines, and MLOps practices.
Experience with Generative AI, LLMs, RAG architectures, and vector databases.
Experience in Healthcare, HealthTech, or SaaS environments.
Familiarity with AI orchestration frameworks and agentic workflows.
Experience with distributed data processing and ML platform engineering.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.
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