Summary
Lead the strategy and delivery of scalable AI and machine learning platforms to accelerate model development and adoption across the organization. Build and mentor a high performing engineering team, collaborate with data science and product partners, and drive operational excellence across the AI ML lifecycle.
Responsibilities
- Define strategy and roadmap for AI ML enablement aligned to business and technology goals.
- Lead development of reusable AI ML tools, frameworks, and infrastructure for model deployment.
- Partner with Data Science Engineering Product and Infrastructure teams to prioritize initiatives and ensure integration.
- Build mentor and grow an engineering team fostering collaboration and accountability.
- Establish best practices for model development deployment monitoring and governance.
- Drive scalability security and ethical AI principles across platforms.
- Stay current with industry trends and evaluate new technologies for adoption.
Requirements
- 10+ years of software engineering experience with at least 5 years in leadership roles.
- Experience leading AI ML or data engineering teams.
- Strong background in AI ML lifecycle management data engineering and cloud architectures (AWS Azure or GCP).
- Bachelor's degree in Computer Science Engineering or related field; advanced degree preferred.
- Proven track record of hiring mentoring and growing engineering teams.
- Excellent collaboration and communication skills with cross functional partners.
- Familiarity with MLOps practices and AI ML frameworks such as TensorFlow PyTorch or Scikit learn.
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