Senior Data Scientist – Applied AI

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Job Category

Software Engineering

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword - it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

About the Team

Our Data Science team builds the next generation of enterprise AI systems powering conversational agents, voice experiences, language models, and intelligent automation. We work across the entire AI stack, from data and model development to evaluation, safety, and production optimization, to deliver reliable, trustworthy AI at enterprise scale.

We're looking for a Senior Data Scientist who is passionate about applying machine learning, statistics, and generative AI to solve complex real world problems. You'll work closely with engineers, product managers, researchers, and business stakeholders to build, optimize, and evaluate AI systems that deliver measurable customer impact.

Responsibilities

Design and execute experiments to evaluate and improve the quality of large language models (LLMs), voice/text AI systems, multimodal models, and long horizon task agents

Build scalable evaluation datasets, benchmarks, and automated evaluation frameworks across language, speech, reasoning, and agent workflows

Analyze large-scale product, customer, and model telemetry to identify failure modes, performance bottlenecks, and opportunities for improvement

Develop statistical models, predictive analytics, and experimentation frameworks to measure model quality, user experience, and business impact

Develop, optimize, and evaluate prompts, system instructions, retrieval strategies, and context engineering techniques to improve performance, reliability, efficiency, and safety of AI applications

Fine-tune and adapt foundation models to improve task specific performance, efficiency, and enterprise readiness using supervised learning, reinforcement learning, and other modern techniques

Design and curate high quality datasets for model training, evaluation, and continuous improvement of AI systems

Partner with cross functional stakeholders to define AI product requirements, success metrics, experimentation strategies, and data driven roadmaps

Build dashboards, analytics pipelines, and reporting frameworks that provide actionable insights into AI quality, reliability, customer experience, and business outcomes

Apply statistical inference, causal analysis, and machine learning techniques to solve challenging product and operational problems

Develop scalable evaluation methodologies for Responsible AI, including safety, robustness, fairness, security, and governance

Communicate technical findings and recommendations clearly to both technical and executive audiences

Preferred Qualifications

5+ years of experience in Data Science, Machine Learning, Applied AI, or a related technical field

Master's or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, Operations Research, Machine Learning, or a related quantitative field, or equivalent practical experience

Strong experience with Large Language Models (LLMs), Generative AI, and AI agents

Experience with prompt engineering, context engineering, and Retrieval-Augmented Generation (RAG)

Experience fine tuning and adapting foundation models for domain specific applications

Experience applying reinforcement learning and modern model optimization techniques

Strong foundation in machine learning, statistics, experimentation, and causal inference

Experience designing A/B tests and interpreting experimental results

Proficiency in Python and common machine learning frameworks

Experience with speech, multimodal AI, conversational AI, or voice agents is a plus

Experience monitoring and continuously improving machine learning models in production

Excellent communication and collaboration skills, with the ability to influence cross functional teams and executive stakeholders

Preferred Skills

Large Language Models (LLMs)

Generative AI

AI Agents

Prompt Engineering

Context Engineering

Foundation Model Fine Tuning

Reinforcement Learning (RL)

Retrieval-Augmented Generation (RAG)

Machine Learning

Statistical Modeling

Experiment Design and A/B Testing

Causal Inference

Predictive Analytics

Python

AI Evaluation and Benchmarking

Responsible AI

Speech and Multimodal AI

Data Visualization

What Makes You Successful

You're a hands on technical expert who enjoys solving challenging AI problems through data, experimentation, and machine learning. You combine strong analytical thinking with practical engineering skills and are comfortable working across the full AI lifecycle, from data curation and model optimization to evaluation and production deployment. You thrive in collaborative environments, communicate effectively with diverse stakeholders, and are driven to build AI systems that are reliable, scalable, and deliver meaningful business and customer value.

Unleash Your Potential

When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future - but to redefine what’s possible - for yourself, for AI, and the world.

Accommodations

If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form .

Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.

Posting Statement

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.

At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.

The typical base salary range for this position is $148,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $285,800 annually.

The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.