
AI Solutions Specialist
2 days ago
About the Role
We're seeking a seasoned expert to oversee the maintenance, optimization, and ongoing performance of deployed AI/ML systems and solutions. In this capacity, you'll serve as a bridge between innovation and operations, ensuring our AI solutions deliver consistent value and operate seamlessly in real-world environments.
Key Responsibilities
- Sustainment: Lead the post-deployment lifecycle of AI solutions, ensuring continued functionality, reliability, and scalability.
- Monitoring Frameworks: Establish monitoring protocols to oversee system performance, usage, and metrics for AI/ML models and APIs.
- Anomaly Detection: Identify 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 objectives.
- 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
- 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 sustenance of 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.
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