Experienced Data Science AI Engineer

This is a fully remote position, open to applicants in Texas.

📋 Description

• Create and develop AI solutions that leverage machine learning models, including Generative AI, Natural Language Processing, and predictive analytics tailored for healthcare applications.

• Design, test, and launch AI solutions in both cloud-based and on-premise environments, ensuring they are reliable, scalable, and impactful in real-world scenarios.

• Manage extensive healthcare datasets, engaging in data preprocessing, feature engineering, and model training while adhering to HIPAA and other regulatory requirements.

• Integrate and enhance AI solutions within Gainwell’s existing technology framework, working in collaboration with engineering teams to ensure smooth integration.

• Continuously track, refine, and improve AI solutions for precision, efficiency, and speed, applying MLOps best practices.

• Keep abreast of the latest advancements in AI and machine learning, investigating new technologies and methodologies to boost solution effectiveness.

• Ensure that AI implementations comply with healthcare industry regulations, ethical AI guidelines, and data privacy standards.

• Discover opportunities to automate workflows and refine business processes through AI-driven solutions.

⛳️ Requirements

• Master’s degree or Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a related discipline.

• Over 5 years of experience in AI and machine learning engineering, with a specialization in developing and deploying AI solutions.

• Practical knowledge in production operations related to machine learning, deep learning, and Generative AI.

• Proficient programming skills in Python, along with experience in AI Agent Frameworks (such as Langchain and Crew.ai), TensorFlow, PyTorch, and other AI frameworks.

• Background in developing, deploying, and fine-tuning large language models (LLMs) such as GPT, Gemini, or Claude for real-world applications, including prompt engineering, model optimization, and improving inference efficiency.

• Familiarity with cloud platforms (AWS, Azure, or GCP) and MLOps for scalable AI deployments.

• Skilled in big data technologies (Spark, Hadoop, SQL, NoSQL databases).

• Strong analytical abilities with the capacity to convert business challenges into AI-driven solutions.

• Knowledge of healthcare AI applications and regulatory compliance (HIPAA, CMS) is advantageous.

🏝️ Benefits

• Generous and flexible vacation policy.

• Educational assistance programs.

• Comprehensive health benefits package.

• 401(k) employer matching.

• Access to leadership and technical development academies.