Senior Manager - Machine Learning - Slack AI

Job Category

Software Engineering

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.

Slack AI's mission is to transform how people work by making Slack an AI-powered operating system. We're tackling significant challenges like unlocking collective knowledge and reducing noise, all while building a seamless, consumer-grade AI experience within users' existing workflows. Join us in shaping the future of work!

Slackbot is Slack's AI assistant that we recently launched to help users find information, get answers, and take action without leaving their workflow. At the heart of Slackbot is our search and retrieval system, which powers the assistant's ability to surface relevant messages, files, and knowledge from across a user's workspace. As Slackbot adoption grows, we're expanding our Search Machine Learning team to drive the next wave of quality improvements—enhancing both the agentic search capabilities that power conversational interactions and the traditional recall mechanisms that ensure users get the most relevant results every time.

We are looking for a highly motivated and experienced Senior Engineering Manager to lead our Search Machine Learning team  this role, you'll be responsible for driving search quality improvements through machine learning and statistical techniques, working at the intersection of agentic and traditional recall search. You will partner closely with search product teams, fellow ML engineers, and ML infrastructure/platform teams to deliver production-ready models that directly enhance how millions of users find information in Slack.

You'll blend strategic technical vision with hands‑on collaboration, guiding your team of machine learning engineers to build innovative solutions that solve real user search problems. A successful candidate will be an experienced engineering leader with a track record of leading high‑performing ML teams and deep knowledge of search systems, machine learning model development, and cross‑functional collaboration needed to ship impactful ML‑powered products.

You'll be accountable for delivering measurable improvements to how users find information in Slack—whether through next‑generation agentic search capabilities or enhanced traditional recall mechanisms. Success in this role requires balancing hands‑on technical leadership with strong people management, fostering a culture of experimentation and impact, and navigating the complexities of shipping ML models in a fast‑paced production environment.

• Define, evolve, and communicate the team's vision, mission, and strategy across Slack.
• Collaborate with Product, Infra, AI/ML and other technical leaders to define and execute on the team's roadmap, including team growth.
• Develop a deep understanding of Slack's AI and ML technical domain to inform engineering possibilities and drive creative technical solutions.
• Mentor and coach engineers to foster their technical growth and leadership potential.
• Own and drive the successful execution of projects.
• Partner effectively with other engineering leaders across the organization to solve high‑priority challenges collaboratively.

• Bachelor's degree in Computer Science, Engineering, a related field, or equivalent practical experience.
• 4+ years of experience as an Engineering Manager leading software development teams.
• Experience managing machine learning engineers and understanding the unique challenges of ML development life cycles (experimentation, model training, evaluation, deployment).
• Deep understanding of search systems and ranking algorithms, with experience shipping search quality improvements at scale.
• Track record of establishing metrics and evaluation frameworks to measure ML model performance and search…