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About the Role
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. 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.
Responsibilities
- 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.
Requirements
- 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.
Skills
- Machine Learning
- Artificial Intelligence
- conversational intelligence
- conversational agentic systems
- retrieval systems
- search algorithms
- vector databases
- embeddings
- RAG solutions
- NLP
- Generative AI
Location
- San Francisco
- New York City
Work Type
- Full-time
Experience Level
- Senior
Salary/Compensations
- $128,500 - $260,100 annually
- $141,200 - $285,800 annually
Benefits
- time off programs
- medical
- dental
- vision
- mental health support
- paid parental leave
- life and disability insurance
- 401(k)
- employee stock purchasing program
About the Company
- Salesforce is the #1 AI CRM, where humans with agents drive customer success together.
- 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.
- Agentforce is the future of AI, and you are the future of Salesforce.
Equal Opportunity
- Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment.
- 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.
- 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.