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Tier-1 brand and metro location increase applicant density, but specialized senior LLM role limits broad competition.
Specialized LLM, RLHF, and distributed training expertise required, so high domain bias.
PhD/Master's and hands-on production LLM, RLHF, distributed training requirements produce strict filtering.
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Own end-to-end development and deployment of large language models (LLMs) and related AI systems powering Salesforce’s AgentForce production AI services.
Lead research and hands-on work in model training, fine-tuning, reinforcement learning, evaluation, optimization, and production readiness for enterprise-scale AI applications.
Collaborate cross-functionally with research, engineering, product, and infrastructure teams to deliver scalable, robust, and high-performance AI solutions used by millions of users.
PhD or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or related field.
Strong hands-on experience in large language model fine-tuning, evaluation, inference optimization, and continuous learning workflows.
Proficiency in Python, deep learning frameworks (PyTorch or TensorFlow), and modern LLM tooling such as Hugging Face, DeepSpeed, Kubernetes.
Work Experience Required: Not explicitly mentioned in the JD (but significant research or industry experience in LLMs, NLP, reinforcement learning, or related areas implied).
Experienced researcher or engineer with a track record of delivering production-scale AI models and systems, especially LLMs and agentic AI workflows.
Comfortable independently driving technical execution in fast-paced, iterative AI environments with strong collaboration across multiple disciplines.
Demonstrates expertise in reinforcement learning, multi-modal AI, AI safety, and distributed training/inference infrastructure.