Software Engineer (Multiple Levels) - Machine Learning Infrastructure, Slack

Software Engineer – ML Infrastructure We are looking for Software Engineers to join the ML Infrastructure focus area and help architect and operate the core systems that power AI at Slack. Responsibilities Design, build, and operate systems to train, serve, and deploy machine learning models at scale, focusing on reliability, performance, and operational simplicity. Evolve GPU‑backed inference infrastructure to support high‑throughput, latency‑sensitive workloads, including large‑scale model serving. Architect and optimize distributed training and data processing systems using platforms such as Ray, Airflow, Spark, or similar technologies. Build and maintain Kubernetes‑based platforms and orchestration layers using tools such as KubeRay, vLLM, and internally developed services. Architect solutions that bridge legacy systems with modern technologies while maintaining monolithic application stability. Develop robust monitoring, observability, and alerting for production ML workloads to ensure operational excellence. Partner closely with AI Platform, ML modeling, security, and product engineering teams to design infrastructure that supports evolving AI use cases. Provide technical leadership through design reviews, mentorship, and by setting engineering standards and long‑term architectural direction for ML infrastructure. Author technical design and architecture documentation, and contribute thought leadership through engineering blog posts. Build and ship high‑quality, production‑grade software using modern engineering practices. Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale. Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably. Critically evaluate code (human or AI‑generated) for correctness, quality, security, and performance. Qualifications Significant professional experience in software engineering with a strong focus on infrastructure, backend systems, platform engineering, or MLOps. Deep experience building and operating distributed systems, with expert‑level knowledge of Kubernetes and container‑based platforms. Hands‑on experience with modern ML infrastructure and serving stacks such as Ray, KubeRay, vLLM, or similar. Experience working with GPU infrastructure, including performance optimization and operational management at scale. Strong experience with data infrastructure and orchestration technologies such as Airflow, Spark, or similar systems. Experience building and operating cloud‑native systems on public cloud platforms such as AWS, GCP, or Azure, including infrastructure as code. Demonstrated ability to drive technical direction for complex systems and balance short‑term delivery with long‑term architectural goals. Excellent written communication and ability to thrive in an asynchronous and globally distributed infrastructure team. A related technical degree is required. Demonstrated, genuine AI‑first approach to engineering, using AI to move faster and contribute well beyond core specialty. Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor) in development workflows. Advanced prompt engineering skills and ability to write precise, structured prompts that cultivate system context for reliable, secure, production‑ready AI outputs. Benefits Salesforce offers a comprehensive benefits package including medical, dental, vision, mental‑health support, paid parental leave, life and disability insurance, 401(k), and employee stock purchasing program. Salary for this role ranges from $148,500 to $313,700 annually, excluding additional bonuses, equity, or other incentives. More details are available at Equal‑Opportunity Employer Salesforce is an equal‑opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment. #J-18808-Ljbffr 100 Salesforce, Inc.