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.
ResponsibilitiesAgentic 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 QualificationsExperience 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.#J-18808-Ljbffr
