Staff Data Scientist - AI/ML

Job Summary

At Semantic Substrate Incubation, we are drowning in data but starving for meaning. As our lead data scientist, you will bridge this "Meaning Gap" by turning raw, chaotic event logs into an intelligent, concept-linked graph—the Semantic Brain. You will move past basic chat interfaces to architect an Identity-Anchored World Model that allows LLMs to understand complex enterprise ideas like "High-Value Churn Risk" and drive autonomous, agentic decisions.

Responsibilities

• Map fragmented data to human-readable terms by leading the discovery and mapping of raw event logs to Vertical Ontologies (Industry Knowledge Packs).
• Accelerate AI accuracy by 60% by designing and deploying a Concept Graph that anchors the substrate, utilizing verified profile IDs instead of session data for memory.
• Train autonomous agents efficiently by building the logic for Reward Signal Extraction and Context-Aware actioning to infer KPIs directly from interaction logs, avoiding traditional delayed-reward bottlenecks.
• Reduce agentic action risk by 40% by utilizing Off-Policy Evaluation (OPE) and action-conditional world models to simulate high-value scenarios and ground recommendations.
• Avoid the "Services Trap" and enable scale by engineering automated systems that allow 80% of the team's context mapping to be executed seamlessly without manual intervention.

Requirements

• A Proven Tracker Record in AI/ML: Broad capability delivering high-impact AI systems at scale (typically requires around 10+ years of professional data science experience).
• Deep Graph Expertise: Hands-on experience designing, implementing, and querying graph databases, with specific, deep technical proficiency in AWS Neptune and SPARQL.
• Prominent Production-Level Data Pipelines: Extensive experience with Apache Spark (PySpark/Scala) for large-scale distributed data processing and ETL optimization on massive datasets.
• Modern LLM Orchestration: Direct, practical experience building sophisticated applications using frameworks like LangChain, LlamaIndex, or equivalent agentic workflows.
• Cloud Architecture: Strong hands-on backend and infrastructure skills utilizing Python and the AWS ecosystem (EC2, Lambda, S3, CloudFormation, CDK, or Terraform).

Qualifications

On Your Resume:

• Proven experience in AI/ML with a focus on delivering high-impact AI systems at scale.
• Hands-on experience with graph databases and AWS Neptune.
• Extensive experience with Apache Spark for large-scale distributed data processing and ETL optimization.
• Direct, practical experience building sophisticated applications using modern LLM orchestration frameworks.
• Strong hands-on backend and infrastructure skills utilizing Python and the AWS ecosystem.

Skills

Preferred Skills:

• Experience with LangChain, LlamaIndex, or similar agentic workflows.
• Expertise in AWS services such as EC2, Lambda, S3, CloudFormation, CDK, or Terraform.
• Knowledge of industry-specific ontologies and vertical knowledge packs.

Benefits

Things You’ll Get:

• Dedicated Growth Time: 10% of your time every quarter on individual engineering growth activities, research exploration, and passion projects.
• Continuous Learning Stipend: An annual stipend for technical books, research papers, and subscriptions to keep your skills at the absolute cutting edge.
• Conference & Publication Support: Fully covered travel and attendance expenses when you are selected to present research or speak at major industry AI conferences.
• Top-Tier Health & Wellness: Comprehensive global health, dental, and vision coverage, alongside flexible time-off policies to ensure you stay energized.

Qualtrics Hybrid Work Model

We gather in the office three days a week; Mondays and Thursdays, plus one day selected by your organizational leader. The rest of the week, work where you want, owning the integration of work and life.

Equal Opportunity Employer

Qualtrics is an equal opportunity employer meaning that all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other protected characteristic. Applicants in the United States of America have rights under Federal Employment Laws: Family & Medical Leave Act, Equal Opportunity Employment, Employee Polygraph Protection Act.