Machine Learning Engineer

Overview

Software Engineering LMTS- MLE role for an experienced Machine Learning Engineer to build Agentforce Retrieval-Augmented Generation (RAG) and generative AI services on Salesforce’s Agentforce Knowledge Foundation team.

What you'll do

• Design and deliver scalable generative AI services integrated with many applications and thousands of tenants.
• Build scalable generative AI system and services for RAG, Enterprise Knowledge Graph, and fine-tuned LLM deployments.
• Drive system efficiencies via automation, including capacity planning, configuration management, performance tuning, monitoring, and root cause analysis.
• Participate in periodic on-call rotations and be available for critical issues.
• Contribute across the end-to-end AI product development lifecycle.
• Partner with product, architects, data scientists, and researchers to define requirements, design prototypes, and bring technologies to production.

What you'll need

• 10+ years of software engineering experience.
• 5+ years of industry experience in ML engineering for building AI systems and/or services.
• Experience with distributed, scalable systems and modern data stack messaging/processing frameworks including Spark/Flink, Hadoop, Kafka, and Docker.
• Strong programming experience in Java and/or Python and familiarity with TensorFlow or PyTorch.
• Experience with LLMs and prompt engineering.
• Knowledge of public cloud Data & AI services and cloud-native architecture patterns (AWS/GCP).
• Good working knowledge of deep learning and machine learning algorithms.