Job
Description
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Job Reference: #LI-JC1 Role Summary: The AI/ML Platform Engineering Lead is a pivotal leadership role responsible for managing the day-to-day operations and development of the AI/ML platform team. In this role, you will guide the team in designing, building, and maintaining scalable platforms, while collaborating with other engineering and data science teams to ensure successful model deployment and lifecycle management. Key Responsibilities: Lead and manage a team of platform engineers in developing and maintaining robust AI/ML platforms. Define and implement best practices for machine learning infrastructure, ensuring scalability, performance, and security. Collaborate closely with data scientists and DevOps teams to optimize the ML lifecycle from model training to deployment. Establish and enforce standards for platform automation, monitoring, and operational efficiency. Serve as the primary liaison between engineering teams, product teams, and leadership. Mentor and develop junior engineers, providing technical guidance and performance feedback. Stay abreast of the latest advancements in AI/ML infrastructure and integrate new technologies where applicable. Qualifications: Bachelor s or Master s degree in Computer Science, Engineering, or a related field. 8+ years of experience in AI/ML platform development and infrastructure. Proven experience in leading engineering teams and driving large-scale projects. Extensive expertise in cloud infrastructure (AWS, GCP, Azure), MLOps tools (e.g., Kubeflow, MLflow), and infrastructure as code (Terraform) Strong programming skills in Python and Node.js , with a proven track record of building scalable and maintainable systems that support AI/ML workflows. Hands-on experience with monitoring and observability tools, such as Datadog, to ensure platform reliability and performance. Strong leadership and communication skills with the ability to influence cross-functional teams. Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
