Lead ML / MLOps Engineer

Lead Machine Learning Engineer (US Location)We’re Salesforce, the Customer Company, inspiring the future of business with AI + Data + CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.Join the Marketing AI/ML Algorithms and Applications team within Salesforce's Marketing organization. In this role, you'll have the opportunity to make an outsized impact on Salesforce's marketing initiatives, helping to promote our vast product portfolio to a global customer base, including 90% of the Fortune 500. By driving state-of-the-art ML solutions for our internal marketing platforms, you'll directly contribute to enhancing the effectiveness of Salesforce's marketing efforts. Your ML expertise will play a pivotal role in accelerating Salesforce's growth. This is a unique chance to apply your passion for ML to drive transformative business impact on a global scale, shaping the future of how Salesforce engages with potential and existing customers, and contributing to our continued innovation and industry leadership in the CRM space.We are seeking an experienced Lead / Staff Machine Learning Engineer to support the development and deployment of high-impact ML model pipelines that measurably improve marketing performance and deliver customer value. In this critical role, you will collaborate closely with Data Science, Data Engineering, Product, and Marketing teams to lead the design, implementation, and operations of end-to-end ML solutions at scale. As a hands-on technical leader, you will own the MLOps lifecycle, establish best practices, and mentor junior engineers to help grow a world-class team that stays at the forefront of ML innovation. This is a unique opportunity to apply your passion for ML and to drive transformative business impact for the world's #1 CRM provider, shaping the future of customer engagement powered by AI.ResponsibilitiesDefine and drive the overall technical ML engineering strategy for the organizationLead the design, development, and deployment of ML model pipelines, in collaboration with Data Science and Data Engineering teamsImplement infrastructure-as-code, CI/CD, monitoring, and automation to ensure reliable and efficient ML operationsOwn the MLOps lifecycle, including establishing best practices, overseeing model deployment processes, and handling occasional on-call support and incident response for production ML systemsCollaborate closely with Product and Marketing teams to understand business requirements, provide technical feasibility input, and ensure ML solutions are aligned with product roadmaps and deliver measurable business impactSupport the rollout of ML features working with Product and MarketingProvide technical leadership to develop a team of ML Engineers, and mentor and guide junior ML Engineers to build a high-performing teamStay at the forefront of ML and data technologies and drive innovationPosition RequirementsMS or PhD in Computer Science, AI/ML, Software Engineering, or related field8+ years of experience building and deploying ML model pipelines at scaleExpert-level knowledge of containerization, orchestration, and workflow management technologies (e.g., Kubernetes, Docker, Apache Airflow) for deploying and managing complex ML pipelines at scaleAdvanced Python skills, including expertise in ML-specific libraries and best practicesExtensive experience with cloud-based ML platforms (e.g., AWS SageMaker, Azure ML, Google Cloud AI)Proven track record in implementing MLOps best practices, including CI/CD, automated testing, and code quality assuranceProficiency in ML frameworks (e.g., TensorFlow, PyTorch, Keras) and MLOps tools (e.g., MLflow, Kubeflow)Expert in cloud infrastructure management, including IaC, monitoring, and big data technologiesExperience in defining and implementing ML governance policiesStrong communication skills, including the ability to explain complex technical concepts to diverse audiences and engage effectively with executive stakeholdersStrong problem-solving skills and ability to translate technical solutions into business valueProven track record of leading ML projects that deliver measurable business value

#J-18808-Ljbffr