Description
We're seeking exceptional Machine Learning Engineers to advance Agentforce's agent capabilities. In this role, you'll develop fully-autonomous agents with planning, reasoning, and verifiable action execution, while enabling tool use, computer use, and code execution at scale, developing memory architecture, and multi-agent interactions. You'll drive innovation at the intersection of research, incubation and product. By creating state-of-the-art solutions, you'll transform how organizations leverage AI in their workflows, applying your expertise to solve real enterprise challenges and shape the future of AI technology.
Responsibilities
Agentic AI System Backend/Frontend Development:
Develop agentic system infrastructure and components, including planning and reasoning engines, tool use, computer use and code execution environments, memory architecture, multi-agent orchestration layer, human-agent interaction, etc.
Design, implement, and tune robust APIs and API framework-related features.
Create visualization interfaces for system demonstration and rapid development iteration.
Prompt Engineering and Optimization:
Design and experiment with creative prompts to optimize the performance of LLMs for specific use cases, ensuring accuracy, relevance, and efficiency. Implement techniques like few-shot learning, chain-of-thought prompting, and context tuning to enhance LLM outcomes for AI agents.
AI Model Development, Evaluation and Deployment:
Finetune AI model for agentic use case.
Develop metrics and tools to evaluate model performance, reliability, and trust.
Deploy LLM models into production systems, ensuring scalability, security, and efficiency.
Collaboration and Research:
As a machine learning engineer from the AI research team, you collaborate with researchers, product managers, engineers, and designers to identify and implement AI-driven solutions for internal incubators. Stay at the forefront of LLM research and emerging technologies to recommend and integrate advancements into Salesforce’s AI strategy.
Educational Background:
Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.
Technical Skills:
Strong expertise in LLMs/MLMs (e.g., GPT, Gemini, Claude, Llama, Mistral, Qwen, Deepseek, etc.) and prompt engineering techniques.
High proficiency in Python programming language. Experience in Java is a plus.
Preferred Qualifications
Experience in developing complex agentic systems using LLMs.
Experience in REST-based API development, API lifecycle management and/or client SDKs development.
Experience in frontend development for system demonstration, such as using tools like Streamlit, Chainlit, etc.
Experience with large-scale reinforcement learning techniques.
Proficiency in popular Deep Learning frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers).
Prior experience in building AI solutions for enterprise software or SaaS platforms.
For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.
