Principal ML Architect / Principal Machine Learning Architect

Job Title: Principal ML Architect / Principal Machine Learning Architect

Location: Nashville, TN (Hybrid)
Duration: Long Term Contract
Rate: Negotiable

Position Overview: The Principal ML Architect of MLOps will play a critical role in our Data Science team, focusing on the development and enhancement of our Machine Learning Operations (MLOps) platform. This role demands a unique blend of cloud architecture expertise, AI/ML knowledge, and leadership skills to lead a team in building and maintaining a robust, efficient, and cutting-edge MLOps platform.

Key Responsibilities:

- Architectural Leadership: Lead the architecture and design of our MLOps platform, with a focus on Google Cloud Platform Vertex AI and Kubeflow related platforms.
- Responsible AI Solutions: Develop solutions focused on Responsible AI, including explainability, data drift detection, and fairness metrics. Ensure adherence to ethical AI practices.
- Developer Experience: Drive enhancements to the MLOps platform to optimize developer experiences for data and ML engineers, incorporating streamlined workflows and advanced tools.
- Collaboration with AI/ML Experts: Collaborate with AI/ML experts across domains such as Computer Vision, NLP, Forecasting, LLMs, and synthetic data. Integrate the latest advancements into the MLOps platform.
- AI/ML Reliability and Observability: Work closely with the AI/ML Reliability engineering team to develop components that ensure the reliability and observability of our platform.
- Experience in Platform Development: Candidates should have prior experience working with platform teams, especially in the data and AI/ML space.
- Cloud Platform Expertise: Proficiency in cloud platforms is essential. Experience in expanding platforms to on-premises and edge deployments is a plus.
- Cross-functional Collaboration: Ability to work closely with peer cloud teams, data scientists, and product managers to align platform development with organizational objectives.

Qualifications:

- Bachelor s or Master s degree in Computer Science, Data Science, AI, or a related field is preferred, but not mandatory for candidates demonstrating significant experience and a proven track record in the field of AI/ML and platform development.; Master's or higher degree is a plus.
- 10+ years of experience in the technology or data field
- Proficient engineering and coding skills in Python and other languages.
- Strong background in AI/ML or Data Sciences technologies and platform development.
- Great multi-disciplinary knowledge of technology space (data, cloud, UI, security)
- Excellent communication, leadership, and project management skills.