Senior Staff Software Engineer, Machine Learning (Multiple Levels/ Principal, Ar

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 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. JD - Senior Staff ML Modeling is looking for a Senior Staff Machine Learning Engineer to craft and implement ML and generative AI powered features that leverage our data to make a fabulous, robust, safe, and valuable product for our users. Our team has built out robust functionality spanning LLM deployment, evaluation, monitoring and quality improvements. We are looking for an expert engineer who has worked in the development of both traditional ML and more recent generative AI solutions to help guide the architecture and development of AI. What you will do: Brainstorm with Product Managers, Designers and 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. Help other engineers actively own features or systems and define their long-term health, while also improving the health of surrounding systems. Collaborate with peers across Engineering to triage bugs and troubleshoot sophisticated production issues across the stack. Mentor other engineers and deeply review code. Improve engineering standards, tooling, and processes. 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 light-hearted 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? You may be a fit for this role if you have: 8 years experience with machine learning and software engineering. Put machine learning models, generative AI or other data-derived artifacts into production at scale, especially for text-based applications. Experience with functional or imperative programming languages: PHP, Python, Ruby, Go, C, Scala or Java. Built with common ML frameworks like pytorch, Keras, XGBoost, Tensorflow or Scikit-learn An analytical and data driven approach, and know how to measure success with complicated ML/AI products. 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 the ability to explain sophisticated technical concepts to designers, support, and other specialists. Strong computer science fundamentals: data structures, algorithms, programming languages, distributed systems, and information retrieval. A bachelor's degree in Computer Science, Engineering, Statistics, Mathematics or a related field, or equivalent training, fellowship, or work experience. Proficient in Python, SQL, and libraries such as TensorFlow, PyTorch, or scikit-learn, with experience in managing large datasets and distributed computing frameworks (e.g., Spark, Kubernetes) Highly skilled with statistical, AI/ML, and agentic techniques to understand behaviors of large scale distributed systems, cloud operations, deriving strategic insights from vast datasets. Hands-on experience with cloud platforms Experience with infrastructure automation tools (e.g., Terraform, CloudFormation) and an understanding of DevOps principles in the context of deploying AI/ML models Experience using telemetry and metrics to drive operational excellence Ability to communicate findings to executives and cross-functional product teams by translating scientifically rigorous analyses towards business impact Ability to learn quickly and deliver high-quality code in a fast-paced, dynamic team environment A meticulous and well versed expert in the area of MLOps including DataOps, ModelOps, CodeOps and Explainability Familiar with Agile development methodology and committed to continual improvement of team performance Effective communication, strong leadership skills, team player who is capable of mentoring and being mentored by others Inventive and creative; on task and able to deliver incrementally and on time Preferred Skills: Deployed production RAG pipelines. Experience in A/B testing and experimentation. Experience with LLM evaluation and monitoring at scale. Experience with search or other ranking-oriented ML features and systems, e.g. recommendations or ads ML. Strong background in a wide range of ML approaches, from Artificial Neural Networks to Bayesian methods. Experience with conversational AI. Expertise in retrieval systems and search algorithms. Familiarity with vector databases and embeddings. Knowledge of demonstrating multiple data types in RAG solutions including structured, unstructured, and graph. Worked on generative AI apps with Large Language Models and possibly fine tuned them or improved quality through other methods. Experience building batch data processing pipelines with tools like Apache Spark, SQL, Hadoop, EMR, Airflow, Dagster, or Luigi. Familiarity with search technologies like Elasticsearch and Solr. Accommodations If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form. 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. For California-based roles, the base salary hiring range for this position is $165,600 to $372,900. 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.