Back
Specialized lead AI role, strong employer brand and common ML/MLOps skillset produce medium applicant competition.
Core ML/MLOps expertise transfers across industries but domain-specific energy use-cases moderately increase sensitivity.
Requires master's degree, production ML experience, and specific MLOps skills making shortlisting highly strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design, implementation, and integration of AI model serving solutions focused on performance, reliability, scalability, and cost optimization.
Develop and standardize serving architectures for AI and Generative AI use cases, including defining safe rollout and rollback strategies.
Provide technical leadership by mentoring engineers, conducting design and code reviews, and ensuring operational readiness for production launches.
Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or related field.
Strong experience delivering production-grade software systems with expertise in Python development.
Experience with containerized, microservice-based architectures, API design/versioning, AWS, CI/CD, and DevOps practices.
Experience mentoring engineers and leading technical initiatives. Work Experience Required: Not explicitly mentioned in the JD.
Experienced in leading complex AI model serving projects with accountability for operational performance and cost efficiency.
Capable of cross-team collaboration with platform, MLOps, Reliability, Security, Data, and Product teams to deliver robust AI solutions.
Comfortable driving technical standards and coaching engineering teams in a fast-evolving AI engineering environment.