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Job Category
Data
Job Details
About Salesforce
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.
Do you have a passion for leveraging AI and machine learning to create transformative solutions? We are seeking a Lead AI Engineer to drive innovation, scale critical AI and data science products, and set new standards in AI excellence. This role will involve spearheading the development of cutting-edge AI solutions and building pro-code agents on the Agentforce platform.
Our team is committed to driving growth for both our company and our customers by harnessing the power of AI on Salesforce’s Agentforce platform. Agentforce offers a host of powerful out-of-the-box capabilities for AI-driven automation and insights. We are enhancing these features through the development of pro-code AI skills. As pioneers in advanced Agentforce use cases, we integrate classical data science and machine learning techniques to develop powerful AI solutions. As Customer Zero of these advanced use cases, we develop AI agents and software development patterns that guide both our internal teams and external customers on how to fully leverage the value of Agentforce.
Key Responsibilities
Machine Learning and AI Development
- Design, implement, and deploy state-of-the-art models, including LLMs and Generative AI frameworks.
- Perform model optimization for performance, scalability, and accuracy.
- Leverage leading libraries like TensorFlow, PyTorch, and Hugging Face for experimentation and production.
- Utilize common AI development frameworks such as LangChain, LlamaIndex, and others to build and optimize AI applications.
- Write clean, maintainable, and highly optimized code while following advanced Git workflows like Gitflow.
- Build and optimize machine learning pipelines with tools like AWS SageMaker, Airflow, or Prefect.
- Containerize applications using Docker and deploy them to cloud platforms.
- Implement robust CI/CD pipelines for seamless machine learning deployments.
- Design and optimize SQL queries and database schemas for efficient data retrieval.
- Develop and manage scalable feature engineering pipelines.
- Architect scalable, fault-tolerant machine learning systems.
- Drive engineering excellence through best practices in clean, modular code and system design.
Team Leadership
- Mentor and guide junior data scientists, fostering a culture of learning and innovation.
- Conduct code reviews and ensure adherence to best practices in software engineering and AI development.
- Establish and enforce standards and best practices for data science workflows.
- Influence stakeholders beyond the data science team, driving organizational alignment on DS/ML standards.
Operational Excellence
- Establish and maintain streamlined, scalable processes for data science solution development.
- Align with company standards to ensure consistency and scalability in AI deployments.
Business Impact
- Collaborate with stakeholders to define problems, metrics, and data-driven solutions.
- Translate complex technical insights into actionable business strategies that deliver measurable value.
Qualifications
Experience and Education
- 5+ years of experience in data science, including deploying AI/ML products at scale.
- Bachelor’s or Master’s degree in Mathematics, Computer Science, or a related field (or equivalent experience).
Technical Expertise
- Mastery of Python for data manipulation, machine learning, and software development.
- Proficiency in ML frameworks like TensorFlow, PyTorch, and scikit-learn.
- Proficiency with AI/ ML frameworks like scikit-learn, LangChain, and Llamaindex.
- Knowledge of software engineering principles and best practices, including version control, code optimization, modular design, and testing methodologies.
- Experience with tools like Docker, AWS SageMaker, and Airflow for pipeline optimization.
- Proficiency in SQL, Spark, and ETL processes.
- Familiarity with Generative AI, LLMs, NLP frameworks, and vector databases.
- Hands-on experience with cloud platforms like AWS.
Soft Skills
- Craft detailed design documents and technical white papers.
- Translate technical concepts into business-friendly language.
- Lead cross-functional discussions and align diverse viewpoints.
- Deliver polished presentations to senior stakeholders.
- Exhibit exceptional problem-solving and leadership abilities.
Why Join Us?
- Work on cutting-edge AI and data science projects with a measurable business impact.
- Collaborate with a talented and passionate team of professionals.
- Grow professionally with access to modern tools, technologies, and resources.
- Be part of a culture that values innovation, collaboration, and growth.
Accommodations
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Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
