Senior Data Science Engineer - Hyperforce Solutions Engineering

$165,600 - $227,700/Yr

Salesforce - San Francisco, CA

Full-time - Senior

San Francisco, CA

Publishing Industries

About the position

Salesforce is seeking a highly skilled and experienced Senior Data Science Engineer to join our dynamic Hyperforce Solutions Engineering team. This role is pivotal in developing data science solutions that enhance developer productivity and drive data-driven decision-making processes. The ideal candidate will lead the development and implementation of advanced data science projects, particularly focusing on building Large Language Model (LLM) applications for internal customers using LangChain. This position requires a deep understanding of transformers, GPT architecture, and the functionalities of LangChain, along with proficiency in A/B testing, Python, SOQL, and REST API. As a Senior Data Science Engineer, you will oversee the entire lifecycle of data science and machine learning solutions, from proof of concept to deployment and ongoing maintenance. You will be responsible for developing conversational AI agents, chatbots, and virtual assistants, integrating these AI agents into existing software systems, and ensuring seamless operation and compatibility. Your role will also involve designing and conducting A/B testing for various experiments and improvements, utilizing statistical tools to analyze test results, and making data-driven decisions to optimize application performance. In addition to technical responsibilities, you will develop and maintain dashboards using tools like Tableau and Splunk to visualize experiment results, making insights accessible to business stakeholders. You will stay up-to-date with the latest industry trends, including llamaindex, mistral, LLAMA3, and other emerging LLMs, and evaluate and incorporate new technologies and methodologies to maintain our competitive edge. Collaboration with cross-functional teams will be essential to identify opportunities for improvement and innovation, and you will also mentor junior data scientists, contributing to the team's knowledge sharing and skill development.

Responsibilities

• Lead the development and implementation of LLM applications using LangChain, focusing on transformers and GPT architecture.
• Develop conversational AI agents, chatbots, or virtual assistants.
• Integrate AI agents into existing software systems and platforms, ensuring seamless operation and compatibility.
• Design and conduct A/B testing for various experiments and improvements.
• Utilize statistical tools to analyze test results and make data-driven decisions to optimize application performance.
• Develop and maintain dashboards using tools like Tableau and Splunk to visualize experiment results.
• Exhibit proficiency in Python and SOQL for data manipulation, analysis, and automation tasks.
• Stay up-to-date with the latest industry trends, including llamaindex, mistral, LLAMA3, and other emerging LLMs.
• Work closely with cross-functional teams to identify opportunities for improvement and innovation.
• Mentor junior data scientists and contribute to the team's knowledge sharing and skill development.

Requirements

• A Master's degree in Computer Science, Computer Engineering, Statistics, Data Science or other relevant courses.
• Minimum of 5 years of experience in a data science role, with a proven track record of developing and implementing LLM applications.
• Demonstrated experience with Deep learning concepts and NLP frameworks such as nltk, pytorch, tensorflow, keras, huggingface, sentence_transformers, etc.
• Deep understanding of transformers, GPT architecture, LangChain functionalities, RAG, and Agent concepts.
• Experience with RAG, Chat Agents and content personalization techniques.
• Extensive experience in A/B testing, statistical analysis and data visualization tools like Tableau and Splunk.
• Experience with ML concepts and statistical libraries like pandas, matplotlib, numpy, sklearn (or their equivalents).
• Demonstrated ease with querying languages like SQL (SOQL / SAQL is a plus).
• Proficiency in handling unstructured data.
• In-depth knowledge of NoSQL databases (e.g., MongoDB, Cassandra).
• Experience with vector databases (e.g., Pinecone, Weaviate).
• Familiarity with knowledge graphs (e.g., Neo4j, RDF).
• Strong knowledge of LLM fine-tuning methods such as PEFT, QLORA, and LORA and prompt engineering.
• Excellent communication and leadership skills, ability to work in a team environment, strong problem-solving abilities, and a proactive approach to tackling challenges.

Nice-to-haves

• Familiarity with the latest industry trends and advancements in data science and machine learning.
• Experience with deploying ML applications on cloud ecosystems like AWS or GCP, and monitoring/enhancing systems in an ongoing fashion.
• Experience with data modeling on RDS / DynamoDB / Hive etc.
• Experience with Kubernetes for deploying and managing scalable ML models.

Benefits

• Competitive salary range of $165,600 to $227,700 based on location and experience.
• Incentive compensation and equity opportunities.
• Comprehensive health insurance coverage.
• Employee resource groups and inclusive benefits.
• Professional development programs and training opportunities.