AI Engineer, Python
Intetics
AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonPyTorchScikit-LearnTensorflow
AI Developer, Healthcare
Medical Review Institute of America, LLC
full-time
Posted on:
Origin: • 🇺🇸 United States
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AWSAzureCloudDockerGoogle Cloud PlatformJavaScriptKubernetesNode.jsPythonPyTorchScikit-LearnTensorflow
About the role
- Lead the design, development, and deployment of AI/ML solutions across the enterprise.
- Collaborate with business, operations, and technology teams to define solution for AI use cases and align solution delivery timelines.
- Partner with internal teams and third-party vendors to develop AI systems that are efficient, compliant, and scalable.
- Lead rapid prototyping efforts to demonstrate the value of AI/ML applications and inform broader adoption.
- Research, design, and implement machine learning models (supervised, unsupervised, reinforcement learning), including deep learning and NLP.
- Conduct data preparation, cleansing, and feature engineering to support AI/ML workflows.
- Train, validate, and fine-tune models to optimize performance, accuracy, and efficiency.
- Build reusable, production-ready pipelines for AI model deployment using MLOps best practices.
- Collaborate with application development team to integrate AI/ML capabilities into existing products and platforms.
- Design and implement robust testing and evaluation frameworks for model validation.
- Monitor, maintain, and continuously improve deployed models to ensure business relevance and performance.
- Ensure all AI systems are secure and compliant with regulatory standards (e.g., HITRUST, SOC 2, HIPAA).
- Support transition of business processes to AI-driven solutions by partnering with operations, training, communications, and customer success teams.
- Provide clear documentation, materials, and support to promote user adoption of AI tools.
- Conduct retrospectives to capture lessons learned and incorporate continuous improvements.
Requirements
- At least 3 years of experience developing and deploying AI/ML models in production environments.
- Experience deploying AI/ML models on cloud platforms (AWS, Azure, or GCP).
- Experience with MLOps practices and tools (e.g., MLflow, Kubeflow, SageMaker, etc.).
- Experience using AI/ML libraries such as TensorFlow, PyTorch, and scikit-learn
- Experience with data preprocessing, feature engineering, and model evaluation techniques.
- Experience in one AI/ML domains such as NLP, computer vision, or time series forecasting.
- Experience working in healthcare (Advantage).
- Proficiency in Python and/or Node.js
- Knowledge of containerization and orchestration (Docker, Kubernetes).
- Knowledge of data structures, algorithms, and software engineering principles.
- Knowledge of healthcare data standards and regulatory compliance, such as HIPAA and HITRUST (Advantage).
- Knowledge of data visualization tools (e.g., Streamlit, Dash) or API development (Advantage).
- Bachelor’s degree in Computer Science, Engineering, or Information Technology.
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