Senior AI/ML Engineer
6 days ago
About Salesforce:
We're a global leader in customer relationship management, empowering businesses to connect with customers in a whole new way. Our mission is to help companies across every industry blaze new trails and connect with customers in a whole new way.
Position: Lead Machine Learning Engineer
Join our Marketing AI/ML Algorithms and Applications team within Salesforce's Marketing organization. In this role, you'll have the opportunity to make a significant impact on our marketing initiatives, helping to promote our vast product portfolio to a global customer base.
Key Responsibilities:
- Technical Leadership: Define and drive the overall technical AI/ML engineering strategy for the organization.
- ML Model Development: Lead the design, development, and deployment of AI/ML model pipelines, in collaboration with Data Science and Data Engineering teams.
- Infrastructure Management: Implement infrastructure-as-code, CI/CD, monitoring, and automation to ensure reliable and efficient AI/ML operations.
- MLOps Lifecycle: Own the MLOps lifecycle, including establishing best practices, overseeing model deployment processes, and handling occasional on-call support and incident response for production AI/ML systems.
- Business Alignment: Collaborate closely with Product and Marketing teams to understand business requirements, provide technical feasibility input, and ensure AI/ML solutions are aligned with product roadmaps and deliver measurable business impact.
- Team Management: Provide technical leadership to develop a team of AI/ML Engineers, and mentor and guide junior AI/ML Engineers to build a high-performing team.
- Industry Expertise: Stay at the forefront of AI and data technologies and drive innovation.
Requirements:
- MS or PhD in Computer Science, AI/ML, Software Engineering, or related field.
- 8+ years of experience building and deploying AI/ML model pipelines at scale.
- Expert-level knowledge of containerization, orchestration, and workflow management technologies.
- Advanced Python skills, including expertise in AI/ML-specific libraries and best practices.
- Extensive experience with cloud-based AI/ML platforms.
- Proven track record in implementing MLOps best practices.
- Proficiency in AI/ML frameworks and MLOps tools.
- Expert in cloud infrastructure management.
- Experience in defining and implementing AI governance policies.
- Strong communication skills, including the ability to explain complex technical concepts to diverse audiences.
- Strong problem-solving skills and ability to translate technical solutions into business value.
- Proven track record of leading AI projects that deliver measurable business value.
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