Senior AI Systems Manager

Job Summary

We are seeking a highly skilled and proactive leader to oversee the maintenance, optimization, and ongoing performance of deployed AI/ML systems and solutions.

This is an exceptional opportunity to join our team as a Senior AI Systems Manager and take on the challenge of driving AI/ML innovation and excellence.

The ideal candidate will have a strong background in AI/ML, with significant experience in developing and sustaining large-scale AI systems. They will possess excellent problem-solving skills, be able to troubleshoot complex AI systems across various domains, and have a proven track record of mentoring and developing junior team members in AI-related roles.

As a Senior AI Systems Manager, you will play a key role in shaping the future of AI at our organization. You will work closely with cross-functional teams to ensure alignment of AI sustainment activities with business goals, communicate effectively with stakeholders to provide updates on system health, risks, and improvements, and define and implement best practices for sustaining AI solutions.

Responsibilities:

• Monitoring & Sustenance: lead the post-deployment lifecycle of AI solutions, ensuring continued functionality, reliability, and scalability.
• Establish monitoring frameworks to oversee system performance, usage, and metrics for AI/ML models and APIs.
• Detect anomalies in AI systems, troubleshoot operational issues, and initiate timely corrective actions.

• Performance Optimization: continuously assess and optimize the performance of AI models to maintain efficiency and accuracy in production environments.
• Collaborate with data scientists and engineers to refine algorithms, retrain models, and update solutions as needed.
• Implement automation where possible to streamline maintenance processes.

• Stakeholder Collaboration: work with cross-functional teams (engineering, product, operations, etc.) to ensure alignment of AI sustainment activities with business goals.
• Communicate effectively with stakeholders to provide updates on system health, risks, and improvements.

• Governance & Best Practices: define and implement best practices for sustaining AI solutions, including documentation, testing protocols, and version control.
• Ensure compliance with ethical AI standards, regulatory guidelines, and established governance frameworks.
• Manage and mitigate risks associated with model drift, data shifts, and system vulnerabilities.

• Incident Management: lead responses to critical incidents involving AI systems by performing root cause analysis and deploying solutions for quick resolution.
• Advocate for proactive risk prevention and early detection strategies.
• Mentor and develop junior team members, fostering their skills in AI observability and domain-specific knowledge in ML, Computer Vision, and Generative AI.

Requirements:

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field; advanced degree preferred.
• 9+ years of experience in machine learning, data science, or software engineering roles, with significant exposure to Computer Vision and Generative AI projects.
• 4+ years of experience specifically focused on AI/ML development and sustain the applications / solutions.
• Strong programming skills in languages such as Python, Java, or Go.
• Extensive experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and cloud platforms (e.g., AWS, Azure, GCP).
• Proficiency in data visualization tools and techniques (e.g., Grafana, Tableau, D3.js).
• Deep understanding of AI/ML concepts, including model training, evaluation, and deployment, with specific knowledge of Computer Vision and Generative AI techniques.
• Experience with monitoring and observability tools such as Prometheus, ELK stack, or similar systems.
• Excellent problem-solving skills and ability to troubleshoot complex AI systems across various domains.
• Proven track record of mentoring and developing junior team members in AI-related roles.

Preferred Qualifications:

• Experience with MLOps practices and tools, particularly for large-scale AI systems.
• Familiarity with AI ethics and responsible AI principles, especially as they relate to Generative AI.
• Knowledge of relevant AI regulations and compliance requirements, including those specific to Computer Vision applications.
• Experience with distributed systems and large-scale data processing for AI applications.
• Contributions to open-source projects or research publications in AI solution at production scale. Previous experience with large-scale AI/ML solutions in production environments.
• Knowledge of DevOps principles and CI/CD pipelines specific to AI/ML systems.

Key Competencies:

• Strong analytical and critical thinking skills
• Excellent communication and collaboration abilities
• Proactive and self-motivated work ethic
• Ability to explain complex technical concepts to both technical and non-technical audiences
• Adaptability and willingness to learn in a rapidly evolving field
• Strong mentorship and leadership skills
• Deep curiosity and passion for AI, particularly in ML, Computer Vision, and Generative AI domains