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Machine Learning Engineer, RAG

Remote San Francisco, CA
USD 172k - 384k
Deep Learning Python TensorFlow Spark Docker Hadoop Machine Learning PyTorch Kafka
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Description

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Job Category

Software Engineering

Job Details

About Salesforce

We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.

Machine Learning Engineer - RAG
Salesforce is looking for a Principal Machine Learning Engineer to be part of Einstein Foundation team building the next-gen Retrieval-Augmented Generation (RAG), leveraging sophisticated generative AI services, pipelines, and components to drive the development and delivery of Agentforce. You will work on and ship impactful generative AI platforms, applications, and products used by millions of people every day.
The Team
We are a group of data scientists, machine learning engineers, and software engineers passionate about designing data products and building intelligent agents that work alongside humans to drive customer success 24/7. We love to learn, teach, and help each other, and we seek individuals with a collaborative attitude and openness to others' ideas.
The Role
You will play a critical role in integrating artificial intelligence and generative AI into advanced RAG technologies, enterprise Knowledge Graphs, and the latest LLM algorithms and technologies to build the next wave of intelligent agents. You will participate in the end-to-end AI product development lifecycle, designing and developing scalable deep learning and generative AI systems and services. You will collaborate with AI Platform Engineers and Software Engineers to define requirements and develop reusable workflows and ML pipelines.
What You’ll Do:
  • Design and deliver scalable RAG services that can be integrated with numerous applications, support thousands of tenants, and operate 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 to resolve critical issues.
  • Collaborate with Product Managers, Application Architects, Data Scientists, and Deep Learning Researchers to understand customer requirements, design prototypes, and bring innovative technologies to production.
  • Engage in fun-spirited yet thought-provoking conversations with your team around fun topics, such as: Should the popularity of penguins influence conservation efforts? Is creativity more like a neural network or a heuristic algorithm? How would society evolve if humans communicated through colors as well as words?
Required Skills:
  • 10+ years of industry experience in ML engineering, building AI systems and/or services.
  • Strong proficiency in NLP and machine learning models.
  • Experience with LLMs and prompt engineering.
  • Proven experience building and applying machine learning models to business applications.
  • Strong programming skills in Python, with experience in machine learning frameworks like TensorFlow or PyTorch.
  • Proven track record to innovate and deliver results at scale.
  • Experience with distributed, scalable systems and modern data storage, messaging, and processing frameworks, such as Kafka, Spark, Docker, and Hadoop.
  • Proven understanding of deep learning and machine learning algorithms.
  • Grit, drive, and a strong sense of ownership, coupled with collaboration and leadership skills.
Preferred Skills:
  • Expertise in retrieval systems and search algorithms.
  • Familiarity with vector databases and embeddings.
  • Experience developing RAG applications/services for sophisticated business use cases and large amounts of unstructured data.
  • Strong background in machine learning engineering and familiarity with pioneering deep learning techniques, particularly in NLP.
  • Expertise in applying LLMs, prompt design, and fine-tuning methods.
  • Strong background in a wide range of ML approaches, from Artificial Neural Networks to Bayesian methods.
  • Experience with conversational AI.
  • Excellent problem-solving skills; the ability to take on problems the world has yet to solve.
  • Strong written and verbal communication skills.
  • Demonstrated track record of cultivating strong working relationships and driving collaboration across multiple technical and business teams.

Accommodations

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Posting Statement

At Salesforce we believe that the business of business is to improve the state of our world. Each of us has a responsibility to drive Equality in our communities and workplaces. We are committed to creating a workforce that reflects society through inclusive programs and initiatives such as equal pay, employee resource groups, inclusive benefits, and more. Learn more about Equality at www.equality.com and explore our company benefits at www.salesforcebenefits.com.

Salesforce is an Equal Employment Opportunity and Affirmative Action Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. Salesforce does not accept unsolicited headhunter and agency resumes. Salesforce will not pay any third-party agency or company that does not have a signed agreement with Salesforce.

Salesforce welcomes all.

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.

For California-based roles, the base salary hiring range for this position is $172,000 to $384,100.

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, benefits. More details about our company benefits can be found at the following link: https://www.salesforcebenefits.com.
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