Salesforce

Technology

LeadAppliedScientistAgentForce

$173–260k United States FULL TIME
The Brief

“Lead Applied Scientist – AgentForce at Salesforce. Skills: Large Language Models, Model development, Reinforcement learning, Production deployment. Own and execute hands-on work across model development. Prepare data”

What You'll Achieve.

Drive measurable model improvements; Meet latency, scalability, reliability, and safety requirements

Industry & Context.

Technology
Problems you'll solve

Failure analysis; Troubleshooting

What They're Looking For.

Must Have

PhD in Computer Science, Machine Learning, AI, or related field, Demonstrated hands-on experience owning full model development lifecycle, Deep expertise in large-scale model training and fine-tuning, Strong background in reinforcement learning, preference learning, or human-in-the-loop learning, Experience building and maintaining continuous learning systems, Solid understanding of model evaluation, alignment, and robustness, Advanced proficiency in Python, Deep experience with PyTorch, TensorFlow or similar, Experience with Hugging Face (Transformers, Accelerate, PEFT), Experience with Distributed training frameworks (DeepSpeed, FSDP, etc.), Experience with ML orchestration and scaling tools (Ray, Kubernetes, internal platforms), Strong data analysis and experimentation skills, Experience mentoring and developing junior researchers or engineers, Strong communication skills across research, engineering, and executive stakeholders

Nice to Have

Strong publication record in top-tier venues or equivalent industry research impact, 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

What You'll Do.

Own and execute hands-on work across model development

Ensure deployment readiness

Lead end-to-end research initiatives on LLM training

Lead end-to-end research initiatives on LLM fine-tuning

Lead end-to-end research initiatives on LLM alignment

Lead end-to-end research initiatives on LLM optimization

Design reinforcement learning pipelines

Implement reinforcement learning pipelines

Iterate on reinforcement learning pipelines

Design continuous learning pipelines

Implement continuous learning pipelines

Iterate on continuous learning pipelines

Conduct rigorous experimentation

Conduct ablation studies

Conduct failure analysis

Drive measurable model improvements

Translate research prototypes into production-grade models

Meet latency requirements

Meet scalability requirements

Meet reliability requirements

Meet safety requirements

Serve as technical POC for AI projects

Drive alignment across research

Define best practices for model training

Define best practices for model fine-tuning

Define best practices for model evaluation

Define best practices for release readiness

Influence architectural decisions

Influence modeling decisions

Mentor junior scientists

Mentor junior engineers

Provide direct technical guidance

Conduct code-level reviews

Foster culture of scientific rigor

Foster culture of reproducibility

Foster culture of ownership

Contribute to Salesforce's external research presence

Engage in collaborations

How You'll Work.

Team & Collaboration

Alignment across teams; Cross-functional teams; Research; Engineering; Product; Platform teams

Communication Scope

Executive stakeholders

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