Lead AI Engineer, ML Systems

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

We are seeking a Lead AI Engineer, ML Systems to join the Salesforce AI Research Incubation Team. In this role, you will own the engineering systems that power model inference, fine-tuning, and evaluation, enabling research models to be reliably deployed and evolved in production environments. You will work closely with AI researchers, agent engineers, and platform teams to support model serving, LoRA-based fine-tuning workflows, and model lifecycle management. This role focuses on production ML systems, not on inventing new model architectures. This is a lead-level individual contributor role with deep ownership of model-facing systems and strong cross-team influence.

Key Responsibilities

• Design, build, and maintain model inference and serving systems, including integration with AI gateways.
• Own and evolve fine-tuning pipelines (e.g., LoRA / PEFT) using internal model tooling.
• Develop and maintain model evaluation, regression detection, and rollout workflows.
• Collaborate with AI researchers to transition research models into production-ready assets.
• Optimize inference systems for latency, throughput, stability, and cost efficiency.
• Implement best practices for model versioning, deployment, rollback, and monitoring.
• Partner with agent and platform engineers to ensure smooth integration between model systems and agent runtimes.
• Provide technical leadership and mentorship on ML system design and operational excellence.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or a related field.
• 5+ years of experience in software engineering, with significant ownership of backend or distributed systems.
• Strong proficiency in Python, with experience building production services.
• Hands-on experience with AI/ML model serving, inference pipelines, or ML systems engineering.
• Experience designing reliable, scalable systems for production environments.
• Familiarity with cloud platforms (AWS, GCP) and containerized environments (Docker, Kubernetes).
• Strong debugging skills across system, data, and model-facing failures.
• Excellent communication skills and ability to collaborate across research and engineering teams.

Preferred Qualifications

• Experience with fine-tuning techniques such as LoRA or PEFT.
• Familiarity with model evaluation frameworks and regression testing.
• Experience with GPU-based workloads or ML infrastructure.
• Knowledge of data formats and pipelines commonly used in ML systems.
• Prior experience working closely with AI research or incubation teams.

Why Join Us?

• Own the systems that turn research models into production AI capabilities.
• Work at the intersection of AI research and large-scale engineering systems.
• Shape how models are trained, deployed, evaluated, and evolved.
• Competitive compensation, benefits, and strong long-term growth opportunities.

Unleash Your Potential

When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.

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Posting Statement

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