Salesforce Sr Data Scientist AI/ML Enterprise Security 

United States, California, San Francisco 

800553606

Job Category

Software Engineering

Job Details

Develop and optimize state-of-the-art AI models to enhance enterprise security.
Design and scale AI infrastructure for high-performance and efficiency.

Responsibilities:

• Analyze large-scale datasets to identify trends, opportunities, and challenges in AI-powered tools and features.

• Develop, optimize, and test machine learning models (predictive, generative, NLP) using cloud platforms such as Salesforce Cloud and AWS SageMaker.

• Build and curate datasets for testing both generative and predictive models in collaboration with cross-functional teams.

• Participate in technical discussions and lead engineering initiatives in Responsible AI, ensuring model fairness and safety before deployment.

• Evaluate and compare tools and libraries (both Salesforce-built and open-source) to determine the most suitable solution for specific use cases.

• Design and implement quantitative metrics to extract insights from structured datasets.

• Develop and maintain reports and dashboards to track key performance indicators (KPIs) and other critical metrics.

• Monitor and analyze log data to detect potential harms, threats, and valuable insights.

• Create data visualizations to effectively communicate insights and trends to stakeholders.

• Ensure data integrity by identifying and resolving discrepancies across structured and unstructured datasets.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.

• 5+ years of hands-on experience in engineering roles focused on Machine Learning, Information Retrieval, Recommendation Systems, Personalization (p13n), Natural Language Processing, Learning to Rank, and Retrieval-Augmented Generation (RAG).

• Proficient in building and prototyping machine learning models and algorithms, with experience wrangling large datasets.

• Skilled in Python and widely used machine learning frameworks, including TensorFlow, PyTorch, scikit-learn, JAX, SciPy, and Pandas.

• Experience deploying and managing AI solutions on cloud platforms such as AWS SageMaker and Amazon Bedrock.

• Experience designing and building microservices, with expertise in Kubernetes, Terraform, Docker, RESTful APIs, and gRPC.

• Strong background in Agile software development and Test-Driven Development (TDD) methodologies.

• Proficient in SQL, shell scripting, and Unix/Linux command-line tools.

• Strong foundation in algorithms, data structures, numerical optimization, data mining, parsing techniques, and high-performance computing.

• Expertise in parallel and distributed computing for scalable AI and ML solutions.

• Deep understanding of fairness in AI, with the ability to implement state-of-the-art and globally recognized fairness evaluation standards, particularly in generative AI.

• Experience in Identity and Access Management (IAM) and Cybersecurity is also preferred.

• Proven ability to work across teams of engineers, data scientists, and researchers to develop and optimize AI-driven solutions.

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Posting Statement

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