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Software Engineering LMTSSalesforce • United States
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Software Engineering LMTS

Salesforce
  • US
    United States
  • US
    United States
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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.
Lead Applied Scientist - AgentForce Team Overview
The
AgentForce Data Science team
powers the
core Large Language Models (LLMs)
behind Salesforce's production-grade AI agents. Our work directly impacts millions of users by enabling trustworthy, scalable, and high-performance AI systems across customer support, sales, marketing, analytics, and internal productivity workflows.
We operate at the intersection of
cutting-edge research and real-world deployment , owning the full
model development lifecycle -from research ideation and training to fine-tuning, evaluation, continuous learning, and production rollout.
Role Overview
We are seeking a
strong Lead/Principal Applied Scientist
to drive advanced LLM research and model development for AgentForce's production services. This role requires
hands-on involvement across the full model development lifecycle , in addition to technical leadership and mentorship.
The ideal candidate is both a
strong individual contributor
and a
technical leader , serving as a primary point of contact (POC) for major AI initiatives while shaping long-term research and modeling strategy.
Key Responsibilities Research, Modeling & Hands-On Execution
Own and execute hands-on work across the full model development lifecycle , including data preparation, model training, fine-tuning, evaluation, iteration, and deployment readiness. Lead end-to-end research initiatives on
LLM training, fine-tuning, alignment, and optimization
for production use cases. Design, implement, and iterate on
reinforcement learning (RL)
and
continuous learning pipelines
(e.g., RLHF, RLAIF, offline/online feedback loops). Conduct rigorous experimentation, ablation studies, and failure analysis to drive measurable model improvements. Translate research prototypes into
production-grade models
that meet latency, scalability, reliability, and safety requirements. Technical Leadership Serve as the
technical POC
for complex AgentForce AI projects, driving alignment across research, engineering, product, and platform teams. Define best practices for model training, fine-tuning, evaluation, and release readiness. Influence architectural and modeling decisions across the AgentForce AI stack. Mentorship & Thought Leadership Mentor junior scientists and engineers through direct technical guidance and code-level reviews. Foster a culture of strong scientific rigor, reproducibility, and ownership. Contribute to Salesforce's external research presence through
publications, talks, and collaborations . Required Qualifications Education & Research Background
PhD in Computer Science, Machine Learning, AI, or a related field . Strong publication record in top-tier venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP) or equivalent industry research impact.
[Nice to have]. Core Technical & Hands-On Requirements
Demonstrated hands-on experience owning the full model development lifecycle , not limited to research or design. Deep expertise in
large-scale model training and fine-tuning , especially for LLMs. Strong background in
reinforcement learning , preference learning, or human-in-the-loop learning. Experience building and maintaining
continuous learning systems
using real-world feedback signals. Solid understanding of
model evaluation, alignment, and robustness
in production environments. Coding & Tooling Advanced proficiency in
Python , with significant hands-on coding experience. Deep experience with PyTorch, TensorFlow or similar deep learning packages. Practical experience with modern LLM tooling, such as: Hugging Face (Transformers, Accelerate, PEFT) Distributed training frameworks (DeepSpeed, FSDP, etc.) ML orchestration and scaling tools (Ray, Kubernetes, internal platforms) Strong data analysis and experimentation skills (NumPy, Pandas, custom evaluation pipelines).
Leadership & Collaboration
Experience mentoring and developing junior researchers or engineers. Strong communication skills across research, engineering, and executive stakeholders. Preferred Qualifications
Experience deploying and iterating on models in
production, high-availability systems . Background in
enterprise AI, agentic systems, or LLM platforms at scale . Familiarity with
trust, safety, or governance frameworks
for AI systems. Experience with large-scale distributed compute environments (multi-GPU / multi-node training). Why Join AgentForce?
Work on
mission-critical LLM systems
at massive scale. Own models
end-to-end , from research to production impact. Shape the future of
enterprise-grade AI agents . Collaborate with world-class researchers and engineers. See your research
ship, scale, and matter .
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
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.
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 $172,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $207,800 - $285,800 annually.The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.
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