1 Athenahealth Technology Lead Member Technical Staff Job

Job Summary:

As the Lead AI/ML Engineer, you will be responsible for designing, developing, and implementing machine learning algorithms and AI solutions that address complex business challenges. You will lead a team of engineers collaborating with cross-functional teams to drive the successful deployment of AI initiatives. Your expertise will be crucial in shaping our AI strategy and ensuring the delivery of high-quality, scalable solutions.

Key Responsibilities:

• Lead the design and development of machine learning models and AI solutions to solve business problems.
• Select appropriate machine learning or deep learning models based on problem context and data availability.
• Develop, train, test, and validate models using state-of-the-art methodologies and frameworks.
• Collaborate with analytics, developers and domain experts to acquire, clean, and preprocess large datasets.
• Engineer features and performs exploratory data analysis to ensure data quality and model readiness.
• Containerize models (Docker/Kubernetes), implement monitoring (Prometheus/Grafana), and automate pipelines (MLflow/Kubeflow).
• Implement models into production environments, ensuring robustness, scalability, and maintainability.
• Develop and maintain CI/CD pipelines for seamless model integration and deployment.
• Monitor and evaluate model performance post-deployment and iterate based on feedback and performance metrics.
• Work closely with cross-functional teams (e.g., product, engineering, Ux, Ax) to align model development with business objectives.
• Stay updated with emerging trends in AI/ML research and tools, integrating best practices into the development process.
• Document model architecture, development processes, and performance evaluations thoroughly.
• Share insights and technical know-how with team members to foster a culture of continuous learning and improvement.
• Research & Innovation: Stay ahead of AI trends (LLMs, generative AI) and advocate for ethical AI practices.
• Develop and implement best practices for model development, testing, and deployment.
• Analyze large datasets to extract insights and improve model performance.
• Communicate complex technical concepts to non-technical stakeholders effectively.
• Ensure compliance with data privacy and security regulations in all AI/ML initiatives.

Qualifications:

• Bachelors or masters degree in computer science, Machine Learning, or a related field.
• Proven experience (5+ years) in AI/ML engineering, with a strong portfolio of successful projects.
• Proficiency in programming languages such as Python, R, or Java, and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of machine learning algorithms, statistical modeling, and data analysis techniques.
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud)
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Strong communication and interpersonal skills, with the ability to lead and inspire a team.
• Experience with version control systems (e.g., Git) and agile development methodologies is a plus.