Software Engineer, Machine Learning (SWE II & SWE I)
Salesforce · California - San Francisco ·
- Category
- ML ai
- Visa sponsorship
- Yes
- Company size
- 1000+
- Salary
- USD 141,200 – 285,800 / year
Salesforce · California - San Francisco ·
Build and deploy ML models for Slack’s conversational AI, ranking, and generative features, using Python, PyTorch, and Spark to drive product impact at scale.
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 EngineeringJob 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 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.
*IN SCHOOL OR GRADUATED WITHIN THE LAST 12 MONTHS? PLEASE VISIT FUTURE FORCE FOR OPPORTUNITIES*
Slack is looking for a Machine Learning Engineer to craft and implement features, services, API methods, and models to leverage our data to make Slack a fabulous, robust, safe, and valuable product for our users. We work on applications across agentic systems (Slackbot), search, recommendation, and more, but ultimately are looking for engineers excited to drive impact at the forefront of conversational intelligence.
We have over 10 million daily active users relying on our product.
At peak usage, a million messages a minute pass through Slack.
During the week, our users spend over a billion minutes a day active in our product.
Machine learning engineers at Slack touch a great variety of parts of our technical stack. At different points, you might find yourself building data pipelines, training recommendation models, fine tuning LLMs, implementing features in our application, or analyzing experiment data. We don’t expect everyone to be an expert in everything, but we are looking for candidates with experience in Machine Learning, a strength in at least a couple of these, and who are excited to learn the rest.
This is a practical machine learning team, not a research team. Our goal is to deliver business value with machine learning and data in whatever form that takes. Sometimes that means bootstrapping something simple like a logistic regression and moving on. Other times that means developing sophisticated, finely tuned models and novel solutions to Slack’s unique problem space. We are looking for engineers who are driven by driving impact for our business, building great products for our customers, and delivering robust, reliable services with machine learning.
Leveraging machine learning and artificial intelligence subject matter expertise to drive improvements in the Slackbot experience.
Develop ML models supporting ranking, retrieval, and generative AI use-cases.
Brainstorm with Product Managers, Designers and Frontend Engineers to conceptualize and build new features for our large (and growing!) user base.
Produce high-quality results by leading or contributing heavily to large multi-functional projects that have a significant impact on the business.
Actively own features or systems and define their long-term health, while also improving the health of surrounding systems.
Support in the development of sustainable data collection pipelines and management of ML features.
Assist our skilled support team and operations team in triaging and resolving production issues.
Mentor other engineers and deeply review code.
Improve engineering standards, tooling, and processes.
Experience with functional or imperative programming languages: PHP, Python, Ruby, Go, C, Scala or Java.
Built with common ML frameworks like PyTorch, Tensorflow, Keras, XGBoost, or Scikit-learn
Fine tuned LLMs or BERT models.
Experience building batch data processing pipelines with tools like Apache Spark, Hadoop, EMR, Map Reduce, Airflow, Dagster, or Luigi.
An analytical and data driven mindset, and know how to measure success with complicated ML/AI products.
Put machine learning models or other data-derived artifacts into production at scale.
Led technical architecture discussions and helped drive technical decisions within the team.
The ability to write understandable, testable code with an eye towards maintainability.
Strong communication skills and you are capable of explaining complex technical concepts to designers, support, and other specialists.
Expertise in conversational agentic systems.
Expertise in retrieval systems and search algorithms.
Familiarity with vector databases and embeddings.
Knowledge of using multiple data types in RAG solutions including structured, unstructured, and knowledge graphs.
Broad experience across NLP, ML, and Generative AI capabilities.
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.
Accommodations
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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 that’s 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.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.

The typical base salary range for this position is $128,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $141,200 - $285,800 annually.

The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.