An AI Performance Manager for Google Cloud Platform (GCP) oversees and enhances the performance of AI systems and applications deployed on the GCP infrastructure. This role involves continuously monitoring, analyzing, and optimizing AI models and algorithms to ensure they are highly efficient and accurate while meeting business objectives. The AI Performance Manager works closely with cross-functional teams, offering insights and guidance on the best practices for AI implementation and scalability within the GCP ecosystem. In addition, this position requires keeping up to date with the latest AI trends and GCP advancements to implement innovative solutions and maintain a competitive edge in AI performance management.
Primary Responsibilities
- Spearhead the tuning and optimization of deep learning models, including large language models, ensuring high accuracy and efficiency. Continuously monitor and enhance the performance of machine learning models. Implement strategies for optimizing computational resources, reducing latency, and increasing overall model effectiveness.
- Must have the right Solution and architecture experience working with Google AI and Data Products BigQuery, Document AI, CCAI, Dialogflow, Vertex AI, Data-prep, etc. or similar products on any other public cloud platforms.
- Design AI architectures and solutions leveraging GCP’s AI/ML capabilities. Lead the development and iterative improvement of machine learning models. Employ robust evaluation metrics to assess model performance and identify areas for refinement.
- Develop and deploy scalable, high-performance AI models and applications. Showcase your Cloud and AI/ML architecture experience when communicating with IT, Product and Data teams.
- Ensure best practices in AI ethics, data security, and compliance. Conduct code reviews, and performance tuning of AI systems. Participate in continuous learning to improve technical skills. Stay abreast of the latest AI trends and advancements, especially within the GCP ecosystem. Provide technical guidance and mentorship to team members.
- Performs other duties as assigned.
Qualifications
Education
Minimum Required:
- Bachelor's Degree in Computer Science, Data Science, AI, Statistics, Information Technology, Engineering, Business, or related field
Experience
Minimum Required:
- 7+ years of experience in delivering complex AI or Data Analytics projects on Cloud Platforms (Google and/or AWS). Hands-on experience in a statistical programming language (e.g. R or Python) and applied machine learning and AI techniques (i.e. computer vision, deep learning, conversational AI, and natural language processing frameworks).
Skills
Minimum Required:
- Experience in systems design with the ability to architect and explain Machine Learning Operations(MLOps) platforms. In-depth knowledge of MLOps principles, practices and methodologies. Proven experience in overseeing and optimizing MLOps platforms, including architecture design and infrastructure management.
- Experience in AI/ML pipelines and CI/CD development is a must. Solid understanding of CI/CD and DevSecOps best practices.
- Expert level experience with containers (Docker) and container orchestration (Kubernetes)
Anticipated Base Pay: $130K-150K + participation in our annual bonus plan.
Benefits:
- Remote Flexibility
- Generous PTO
- 13 Paid Holidays
- 22 Weeks of Maternity Leave
- 4 Weeks of Family Bonding
- Medical / Dental / Vision Insurance
- 401K with Employer Match
Disclaimer:
The salary/pay rate listed is a good faith determination that may be offered to a successful applicant for this position at the time of this job advertisement based on company hiring process and budget for this role and may be modified in the future. Actual compensation may vary from posting based on geographic location, work experience, education and/or skill level.
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Primary Location: United States of America-Texas-Dallas
Work Locations: VIRTUAL EMPLOYEES
Job: Data Operations
Organization: Data Strategy & Analytics
: Full-time
Travel: No
Job Posting: Feb 13, 2024, 10:32:39 AM