AI Systems Reliability Engineer

Job Overview

We are seeking a highly skilled and proactive AI Solutions SRE Lead to oversee the maintenance, optimization, and ongoing performance of deployed AI/ML systems and solutions. The ideal candidate will possess a strong background in machine learning, data science, or software engineering roles, with significant exposure to Computer Vision and Generative AI projects.

Main Responsibilities:

• Lead the post-deployment lifecycle of AI solutions, ensuring continued functionality, reliability, and scalability. This involves establishing 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 to maintain system health and prevent downtime.

Performance Optimization:

• Continuously assess and optimize the performance of AI models to maintain efficiency and accuracy in production environments. This requires collaborating with data scientists and engineers to refine algorithms, retrain models, and update solutions as needed.
• Implement automation where possible to streamline maintenance processes and improve overall system reliability.

Stakeholder Collaboration:

• Work with cross-functional teams (engineering, product, operations, etc.) to ensure alignment of AI sustainment activities with business goals. Effective communication is crucial in this role, as you will need to provide updates on system health, risks, and improvements to stakeholders.
• Communicate effectively with stakeholders to provide updates on system health, risks, and improvements. This includes providing regular status reports and making recommendations for process improvements.

Governance & Best Practices:

• Define and implement best practices for sustaining AI solutions, including documentation, testing protocols, and version control. This ensures that AI systems are maintained in accordance with industry standards and regulatory requirements.
• Ensure compliance with ethical AI standards, regulatory guidelines, and established governance frameworks. This includes managing and mitigating 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. Your ability to analyze complex technical issues and develop effective solutions will be essential in this role.
• Mentor and develop junior team members, fostering their skills in AI observability and domain-specific knowledge in ML, Computer Vision, and Generative AI.

Key Qualifications:

• 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 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.
• 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 SKILLS:

• 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
• We are looking for a passionate and innovative individual who can help us build robust, transparent, and reliable AI systems while nurturing the growth of our team. If you have a strong background in AI/ML, with specific expertise in Computer Vision and Generative AI, and a keen interest in observability and system reliability, we encourage you to apply.