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Salesforce

Lead ML / MLOps Engineer

Salesforce, San Francisco, California, United States, 94199


Lead Machine Learning Engineer (US Location)

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.

Responsibilities:

Define and drive the overall technical ML engineering strategy for the organization.

Lead the design, development, and deployment of ML model pipelines, in collaboration with Data Science and Data Engineering teams.

Implement infrastructure-as-code, CI/CD, monitoring, and automation to ensure reliable and efficient ML operations.

Own the MLOps lifecycle, including establishing best practices, overseeing model deployment processes, and handling occasional on-call support and incident response for production ML systems.

Collaborate 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 impact.

Support the rollout of ML features working with Product and Marketing.

Provide technical leadership to develop a team of ML Engineers, and mentor and guide junior ML Engineers to build a high-performing team.

Stay at the forefront of ML and data technologies and drive innovation.

Position Requirements:

MS or PhD in Computer Science, AI/ML, Software Engineering, or related field.

8+ years of experience building and deploying ML model pipelines at scale.

Expert-level knowledge of containerization, orchestration, and workflow management technologies (e.g., Kubernetes, Docker, Apache Airflow).

Advanced Python skills, including expertise in ML-specific libraries and best practices.

Extensive 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 assurance.

Proficiency 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 technologies.

Experience in defining and implementing ML governance policies.

Strong communication skills and strong problem-solving skills.

Proven track record of leading ML projects that deliver measurable business value.

If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form.

Salesforce is an Equal Employment Opportunity and Affirmative Action Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status.

For Washington-based roles, the base salary hiring range for this position is $176,800 to $243,100.

For California-based roles, the base salary hiring range for this position is $192,900 to $265,200.

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, benefits.

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