Senior 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 Senior Applied Scientist to contribute to advanced LLM research and model development for AgentForce’s production AI services.

This role requires strong hands-on involvement across the full model development lifecycle, including model training, fine-tuning, evaluation, reinforcement learning, optimization, and deployment support. The ideal candidate is a strong individual contributor who can independently drive technical execution while collaborating closely with research, engineering, product, and infrastructure teams.

The candidate will work on production-scale AI systems supporting enterprise-grade agentic workflows, reasoning systems, evaluation services, and multi-modal AI capabilities.

Key Responsibilities

Research, Modeling & Hands-On Execution

• Execute hands-on work across the full model development lifecycle, including:

  • Data preparation and curation

  • Synthetic data generation

  • Model training and fine-tuning

  • RLHF / RLAIF workflows

  • Evaluation and benchmarking

  • Error analysis and iteration

  • Inference optimization

  • Deployment readiness

• Contribute to research and development efforts for:

  • Large language models

  • Tool-calling systems

  • Agentic reasoning workflows

  • Multi-modal AI models

  • Evaluation and guardrails systems

  • Continuous learning pipelines

• Design and implement experimentation pipelines for:

  • Reinforcement learning

  • Preference optimization

  • Alignment tuning

  • Offline and online feedback learning

• Conduct rigorous experimentation, benchmarking, and failure analysis to improve:

  • Accuracy

  • Latency

  • Reliability

  • Robustness

  • Cost efficiency

• Translate research ideas into scalable production-ready AI solutions.

• Support optimization initiatives including:

  • Quantization

  • Distillation

  • Distributed inference optimization

  • Throughput and serving efficiency improvements

Technical Collaboration

• Partner with senior scientists, engineers, and product teams to deliver production AI solutions.

• Contribute to model training, evaluation, release readiness, and production support processes.

• Collaborate with infrastructure teams on scalable training and inference workflows.

• Help define and improve best practices for:

  • Model evaluation

  • Experiment tracking

  • Data quality

  • Continuous learning

  • Production monitoring

• Participate in technical reviews, roadmap discussions, and cross-functional planning efforts.

Mentorship & Growth

• Mentor junior team members through technical guidance and collaboration.

• Contribute to a strong culture of:

  • Scientific rigor

  • Ownership

  • Reproducibility

  • Fast iteration

  • Operational excellence

• Stay current with advancements in:

  • LLMs

  • Reinforcement learning

  • Agentic AI

  • Multi-modal AI

  • Distributed AI systems

• Contribute to internal technical knowledge sharing and innovation initiatives.

Required Qualifications

Education & Research Background

• PhD or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.

• Strong research or industry experience in areas such as:

  • LLMs

  • NLP

  • Reinforcement learning

  • Multi-modal AI

  • Agentic systems

Core Technical & Hands-On Requirements

• Demonstrated hands-on experience in model development, training, fine-tuning, evaluation, and experimentation.

• Strong expertise in:

  • Large language model fine-tuning

  • Model evaluation

  • Inference optimization

  • Continuous learning workflows

• Experience with:

  • Reinforcement learning

  • Preference learning

  • Human-in-the-loop systems

  • Production AI evaluation

• Understanding of:

  • AI safety

  • Guardrails

  • Reliability

  • Production AI systems

• Experience working with distributed training or large-scale inference systems.

Coding & Tooling

• Strong proficiency in Python with solid software engineering fundamentals.

• Experience with:

  • PyTorch

  • TensorFlow

• Familiarity with modern LLM tooling and infrastructure, including:

  • Hugging Face (Transformers, PEFT, Accelerate)

  • DeepSpeed

  • FSDP

  • Ray

  • Kubernetes

  • vLLM

• Strong experimentation and data analysis skills using:

  • NumPy

  • Pandas

  • Custom evaluation pipelines

Leadership & Collaboration

• Strong collaboration and communication skills across:

  • Research

  • Engineering

  • Product

  • Infrastructure teams

• Ability to independently drive technical projects and deliver high-quality execution.

• Comfortable working in fast-moving, highly iterative AI development environments.

Preferred Qualifications

• Experience deploying and supporting production AI systems at scale.

• Background in:

  • Enterprise AI systems

  • Agentic AI workflows

  • Tool-calling systems

  • Multi-agent systems

• Familiarity with:

  • AI trust and safety systems

  • Governance frameworks

  • Responsible AI practices

• Experience with:

  • Multi-modal AI

  • Long-context models

  • Retrieval-augmented systems

  • Planner and reasoning systems

• Experience with multi-GPU or distributed compute environments.

Why Join AgentForce?

• Work on mission-critical AI systems operating at massive enterprise scale.

• Build and deploy production-grade LLM systems used by millions of users.

• Collaborate with world-class researchers and engineers.

• Solve challenging problems in reasoning, reinforcement learning, multi-modal AI, and agentic systems.

• See your work directly impact real-world AI products and enterprise customers.