Gainwell Technologies

Principal Data Sciences

Gainwell Technologies

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $124,000 - $177,100 per year

Job Level

Lead

Tech Stack

AWSAzureCloudGoogle Cloud PlatformHadoopNoSQLPythonPyTorchSparkSQLTensorflow

About the role

  • AI Model Development – Design, build, and train machine learning and deep learning models, including GenAI, NLP, and predictive analytics solutions for healthcare applications. End-to-End AI Solution Deployment – Develop, test, and deploy AI solutions in cloud and on-premise environments, ensuring reliability, scalability, and real-world impact. Data Engineering & Processing – Work with large healthcare datasets, performing data preprocessing, feature engineering, and model training while ensuring compliance with HIPAA and other regulatory standards. System Integration – Implement and optimize AI models within Gainwell’s existing technology stack, collaborating with software engineers to ensure seamless integration. Performance Optimization – Continuously monitor, refine, and optimize AI models for accuracy, efficiency, and speed, leveraging MLOps best practices. AI Research & Innovation – Stay updated with the latest AI/ML advancements, exploring new technologies and methodologies to enhance solution effectiveness. Compliance & Security – Ensure AI implementations adhere to healthcare industry regulations, ethical AI principles, and data privacy standards. Automation & Workflow Enhancement – Identify opportunities to automate workflows and optimize business processes using AI-driven solutions.

Requirements

  • Master’s or Ph.D in Computer Science, AI, Data Science, or a related field. 5+ years of experience in AI/ML engineering, with a focus on developing and deploying AI solutions. Hands-on expertise in machine learning, deep learning, GenAI, NLP, and computer vision. Strong programming skills in Python, TensorFlow, PyTorch, and other AI frameworks. Experience developing, deploying and finetuning LLMs (GPT, Gemini, Claude or similar) for real world applications including prompt engineering, model optimization and inference efficiency. Experience with cloud platforms (AWS, Azure, or GCP) and MLOps for scalable AI deployments. Proficiency in working with big data technologies (Spark, Hadoop, SQL, NoSQL databases). Strong problem-solving skills with the ability to translate business challenges into AI-driven solutions. Knowledge of healthcare AI applications and regulatory compliance (HIPAA, CMS) is a plus.