Machine Learning Engineer, Salesforce

• 2+ years of industry experience of ML engineering in building AI system and/or services
• Experience with LLMs and prompt engineering
• Strong experience building and applying machine learning models for business applications
• Strong experience programming in Python, and using machine learning frameworks such as TensorFlow or PyTorch
• Proven ability to implement, operate, and deliver results via innovation at large scale
• Experience with distributed, scalable systems and modern data storage, messaging and processing frameworks, including Kafka, Spark, Docker, Hadoop, etc
• Good working knowledge of Deep Learning and Machine Learning algorithms. In the very least, you have a strong interest in this domain, as exemplified by coursework you've taken and personal projects you developed
• Grit, drive and a strong feeling of ownership coupled with collaboration and leadership

Desirable

• Salesforce is looking for Machine Learning Engineers to build generative AI services, pipelines and components to enable the development and delivery of Einstein GPT vision. You will work on and ship impactful generative AI platform, applications and products used by millions of people every day
• You will play a critical role in incorporating artificial intelligence and generative AI into the Salesforce. You will participate in the end-to-end AI product development lifecycle
• You will design and develop the scalable deep learning and generative AI system and services, and partner with AI Platform Engineers, Software Engineers to define requirements, design and develop reusable workflow and ML pipeline
• Design and deliver scalable generative AI services that can be integrated with many applications, thousands of tenants, and run at scale in production
• Drive system efficiencies through automation, including capacity planning, configuration management, performance tuning, monitoring and root cause analysis
• Participate in periodic on-call rotations and be available for critical issues
• Partner with Product Managers, Application Architects, Data Scientists, and Deep Learning Researchers to understand customer requirements, design prototypes, and bring innovative technologies to production
• Participate in meal conversations with your team members about really important topics, such as: Should the cuteness of panda bears be a factor in their survivability? Is love a decision tree or a regression model? How far ahead would society be today if we had 12 fingers instead of 10?