Senior/Staff Software Engineer- Machine Learning Infrastructure, Slack

Slack Technologies LLC

Atlanta, GA

JOB DETAILS
SALARY
$172,500–$313,700 Per Year
SKILLS
Amazon Web Services (AWS), Architectural Services, Artificial Intelligence (AI), Artificial Intelligence (AI) Agents, Blog, Business Performance Management, Cloud Computing, Communication Skills, Customer Relationship Management (CRM), Data Processing, Distributed Computing, Documentation, GCP (Good Clinical Practices), GPU (Graphics Processing Unit), High Throughput, Machine Learning, Machine Tool, Mentoring, Microsoft Windows Azure, Open Source, Operating Systems, Performance Tuning/Optimization, Product Engineering, Public Cloud, Salesforce.com, Slack, Software Administration, Software Engineering, System Operations, Systems Maintenance, Technical Leadership, Technical/Engineering Design, Thought Leadership, Training/Teaching, Use Cases, Writing Skills
LOCATION
Atlanta, GA
POSTED
30+ days ago

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category: Software Engineering

Job Details ------------

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 were looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforces 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.

About Slack AI -------------

Slack AIs mission is to transform how people work by making Slack an AI-powered operating system. Were 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 through AI.

About the Team --------------

The AI and ML Infrastructure team is part of Slack's Core Infrastructure organization and is responsible for the foundational systems that enable machine learning and AI across the company. The team designs, builds, and operates reliable, scalable, and high performance platforms that allow product and ML teams to develop, deploy, and operate AI-driven capabilities with confidence.

Core Focus Areas ----------------

### ML Infrastructure

The ML Infrastructure focus area is responsible for the low-level systems that power training and inference at scale. This includes architecting and maintaining distributed systems for model training, serving, and deployment using Kubernetes-based platforms, GPU infrastructure, and open-source ML stacks such as KubeRay and vLLM. The team delivers platform capabilities that improve the speed, reliability, and quality of ML development, including training pipelines, feature generation systems, and compute orchestration.

### AI Platform

The AI Platform focus area builds the tooling and platform layers that enable AI development across Slack. This includes creating developer-facing tools, SDKs, and workflows that allow product teams to integrate AI into Slack features efficiently and safely. The platform supports LLM efficiency and model transition initiatives through integrations with managed services across multiple cloud providers acting as the connective layer between core infrastructure and product engineering teams.

About the Role --------------

We are looking for a Senior or Staff Software Engineer to join the ML Infrastructure focus area and help architect and operate the core systems that power AI at Slack. In this role, you will own foundational infrastructure for large-scale model training and inference, and evolve it into a reliable, secure, and self-service platform used across the company.

Responsibilities ----------------

  • Design, build, and operate systems to train, serve, and deploy machine learning models at scale, with a focus 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

Requirements ------------

  • 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, including expert-level knowledge of Kubernetes and container-based platforms
  • Hands-on experience with modern ML infrastructure and serving stacks such as Ray or KubeRay, vLLM, or similar training and inference orchestration frameworks
  • 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, as well as ability to thrive in an asynchronous and globally distributed infrastructure team

Unleash Your Potential ----------------------

When you join Salesforce, youll 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, well 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 whats possible - for yourself, for AI, and the world.

Accommodations --------------

If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form.

Posting Statement -----------------

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace thats inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence, and qualifications - without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well, including time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.

The typical base salary range for this position is $172,500 - $313,700 annually.

About the Company

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Slack Technologies LLC