Data Scientist - Hyperforce Solutions Engineering

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Job Category: Software Engineering

Job Details

About Salesforce

We’re Salesforce, the Customer Company, driving the future of business with AI, Data, and CRM. Committed to our core values, we help businesses across all industries forge new paths and connect with customers like never before. We empower you to be a Trailblazer too—enhancing your performance, advancing your career, and making a positive impact on the world. If you believe in business as a powerful platform for change and in companies doing both well and good, you’ve found the right place.

Senior Data Scientist / Data Scientist

Join Salesforce as a Senior Data Scientist / Data Scientist in the Bay Area and help us revolutionize developer productivity with innovative data science solutions. Our team is dedicated to creating and supporting machine learning (ML) products such as generative AI chatbots, semantic search, error identification tools, customer support dashboards, and more. Your role will encompass the lifecycle of ML solutions from proof of concept (POC) to deployment and ongoing maintenance.

The Team: Salesforce Hyperforce Solutions Engineering (HSE)

Salesforce HSE develops and hosts the Falcon continuous delivery (CD) and deployment platform. This includes services like Spinnaker, PCS, FIT, and IAC, alongside the ecosystem surrounding these services. Our HDPS Customer Success team helps Salesforce engineers adopt and effectively use HDPS services to ensure successful onboarding, issue diagnosis, training content development, and creating customer-oriented solutions.

Key Responsibilities

LLM Application Development: Lead and implement LLM applications using LangChain, focusing on transformers and GPT architecture. Enhance application functionalities with LLM, Prompt Engineering, RAG, and Agent concepts. Develop conversational AI agents, chatbots, or virtual assistants and ensure seamless integration into existing systems.

Experimentation and Testing: Design and conduct A/B testing, analyzing results with statistical tools to optimize application performance.

Data Analysis and Visualization: Develop dashboards with tools like Tableau and Splunk to make experiment results accessible to business stakeholders.

Programming: Use Python and SOQL for data manipulation, analysis, and task automation, ensuring code quality and maintainability.

Research and Development: Stay updated with industry trends such as llamaindex, mistral, LLAMA3, and other emerging LLMs. Incorporate new technologies to maintain competitive advantage.

Collaboration and Leadership: Work with cross-functional teams to drive innovation, mentor junior data scientists, and contribute to team knowledge sharing.

Required Skills (Data Scientist)

* Master's degree in Computer Science, Computer Engineering, Statistics, Data Science, or related fields.

* Minimum 5 years of experience in data science, specifically in LLM applications.

* Deep learning expertise and proficiency in NLP frameworks like nltk, PyTorch, TensorFlow, Keras, and more.

* Extensive experience with transformers, GPT architecture, LangChain, RAG, and Agent concepts.

* Proven skills in A/B testing, statistical analysis, and data visualization tools like Tableau and Splunk.

* Strong understanding of ML concepts and statistical libraries such as pandas, matplotlib, numpy, and sklearn.

* Proficiency in querying languages, with a preference for SQL, SOQL, or SAQL.

* Experience with unstructured data and NoSQL databases like MongoDB and Cassandra.

* Familiarity with vector databases like Pinecone and Weaviate, and knowledge graphs like Neo4j.

* Up-to-date with the latest industry trends and LLM fine-tuning methods such as PEFT, QLORA, and LORA.

* Excellent communication, leadership, and problem-solving skills, with the ability to work collaboratively in a team environment.

* Experience with ETL pipelines and frameworks like Jenkins, Airflow, or Terraform.

* Prior experience deploying ML applications on cloud platforms like AWS or GCP, and managing scalable ML models with Kubernetes.

Accommodations

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Posting Statement

At Salesforce