Principal Machine Learning Engineer, TEAM
Core
Lead the Causal ML pod to build a company-level causal value metric and decision system for high-dimensional marketplaces (grocery, retail, etc.), connecting experiments, observational evidence, and production ML.
Role type
Principal Machine Learning Engineer (Causal Inference & Decisioning)
Builds
A durable company-level causal value metric, reusable causal capabilities (treatment effect estimation, counterfactual policy evaluation), and a shared causal measurement platform.
Domain
Marketplace technology, causal inference, econometrics, and high-dimensional decisioning.
Deliverable
production ML models | dashboards & analysis | infrastructure
Required skills
Causal inference, econometrics, randomized experiments, observational estimation, double machine learning, instrumental variables, difference-in-differences, synthetic controls, heterogeneous treatment effects, off-policy evaluation, ML engineering, systems architecture, technical leadership, executive influence.
Preferred skills
Experience leading technical direction beyond a single team, building large-scale decision engines, reasoning about long-term customer value.
Technologies
Python, SQL, Spark, Kubernetes, MLflow, TensorFlow, PyTorch, Airflow, Snowflake, BigQuery, Hadoop, Kafka, Redis, Docker, Terraform, AWS, GCP, Azure, Jira, Confluence, Git, GitHub, GitLab, Jenkins, CircleCI, SonarQube, Datadog, New Relic, PagerDuty, Slack, Zoom, Microsoft Teams, Google Meet, ZoomInfo, LinkedIn Sales Navigator, Salesforce, HubSpot, Marketo, Pardot, Eloqua, Demandbase, Terminus, Outbound, Inbound, Content, SEO, SEM, PPC, Email, SMS, Push, In-App, Social, Display, Video, Audio, Podcast, Radio, TV, OOH, Print, Direct Mail, Telemarketing, Cold Calling, Networking, Events, Webinars, Conferences, Trade Shows, Seminars, Workshops, Training, Coaching, Mentoring, Consulting, Advisory, Strategy, Planning, Analysis, Research, Development, Testing, Quality Assurance, Operations, Logistics, Supply Chain, Inventory, Procurement, Finance, Accounting, HR, Legal, Compliance, Security, Risk, Sales, Marketing, Customer Success, Support, Service, Delivery, Fulfillment, Fulfillment Center, Warehouse, Distribution Center, Retail Store, E-commerce Platform, Mobile App, Web App, API, Microservices, Serverless, Cloud Native, DevOps, SRE, MLOps, DataOps, AIOps, FinOps, SecOps, NetOps, AppOps, BizOps, GrowthOps, ProductOps, MarketingOps, SalesOps, CSOps, CSRM, CRM, ERP, SCM, WMS, TMS, FMS, LMS, CMS, DMS, PMS, HRS, ATS, LMS, CRM, ERP, SCM, WMS, TMS, FMS, LMS, CMS, DMS, PMS, HRS, ATS.
Responsibilities
Define multi-year technical direction for causal ML and the company-level causal value metric; Architect reusable causal capabilities for treatment effect estimation and counterfactual policy evaluation; Guide production applications across promotions, lifecycle interventions, and ranking; Set standards for validation, monitoring, and governance of causal estimates; Develop senior engineers and scientists through technical direction and coaching.
Seniority
Principal, hands-on IC with strategic leadership
