Note: The job is a remote job and is open to candidates in USA. Theta is hiring a Head of Engineering and Applied AI to scale its engineering systems and lead its data science team. The role focuses on building reliable model execution and deployment, improving data pipelines, developing AI-assisted workflows, and working with clients’ technical teams.

Responsibilities

• Architecting reliable execution of thousands of models on our cloud and working with client engineering teams to package and deploy our models in their own environments
• Making our pipeline from raw client files to validated model outputs reliable and reusable, while developing AI-assisted workflows for data preparation and modeling
• Setting standards for testing, validation, and reliable deployment, and reviewing the team’s code and designs
• Deciding what we build, automate, or bring in outside help for, while ensuring the team can maintain what gets built
• Helping data scientists resolve difficult client delivery problems and contributing directly when engagements overlap

Skills

• You've built and operated production data or ML systems end to end, at scale on cloud infrastructure (GCP preferred, AWS, Azure, Databricks, or Snowflake is also relevant)
• You've solved problems across data preparation, model execution, and infrastructure, from messy input files to slow model runs
• You check data and outputs critically and know which issues should stop a run
• You're willing to learn and work in our existing R-based production stack
• You think like a product engineer, building around how data scientists and clients actually work and balancing reliability, usability, and delivery needs
• You can lead a small, experienced data science team through hands-on technical guidance and resolving difficult delivery problems
• You're comfortable participating in client calls to explain technical methods and trade-offs, discuss data requirements, and understand clients' technology stacks and infrastructure
• You have a genuine interest in developing AI-assisted workflows, learn unfamiliar tools quickly, and critically evaluate their outputs
• GCP preferred
• Experience building and evaluating AI-assisted workflows for data preparation and modeling, including LLM or agent-based systems
• Production R experience, including packaging, dependency management, containers, or C++ integration through Rcpp
• Statistical modeling, especially familiarity with CLV or BTYD models
• Experience deploying data or modeling workflows in client-controlled environments, including work with Databricks, Snowflake, or Spark
• Infrastructure as code experience, such as Terraform or similar, and CI/CD

Benefits

• Remote (within location)

Company Overview

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