Top Tech Jobs & Startup Jobs in Charlotte, NC

Own revenue-focused data science from opportunity sizing through production ML. Investigate and measure product changes, build and operate batch and online ML systems for personalization, experimentation, and automation, and partner cross-functionally to integrate models into user-facing products. Establish monitoring, lineage, reproducibility, and security practices; improve data pipelines; mentor data scientists; and define ML development best practices while using AI tools to accelerate delivery.

Advise ads product, engineering, marketing, and sales teams on privacy, consumer protection, content regulation, and product development matters. Counsel the advertising business on GDPR, CCPA, international regulations, content policies, and risk management. Monitor regulatory trends and collaborate cross-functionally to support compliant ad-tech products and services.

Build and own Android growth and monetization experiments across subscriptions, advertising, purchases, and upgrade flows. Partner with product, design, data science, and analytics to instrument experiments, evaluate results, and ship reliable experiences at consumer scale. Use AI-native workflows for specification, coding, testing, and review; improve mobile engineering practices; contribute to architecture and code reviews; participate in on-call; and mentor engineers.

Build and operate scalable backend services for connected devices, including device connectivity, telemetry ingestion, health monitoring, command and control, and data pipelines. Collaborate with firmware, mobile, and product teams on APIs and workflows. Use AWS, microservices, streaming systems, observability tools, and AI coding agents to deliver reliable features, participate in incident response, and improve automation and engineering practices.

Design and run high-volume experiments across subscription and monetization experiences, including pricing, trial conversion, SKU routing, churn prevention, and win-back. Translate ambiguous briefs into testable hypotheses, collaborate with product, engineering, data science, and content teams, define success metrics, interpret results, and present learnings. The role requires strong visual and interaction design craft, animation skills, organized Figma files, proactive ideation, and effective use of AI and experimentation tools.

Manage Life360’s patent and trademark portfolios, including prosecution, enforcement, and outside counsel relationships. Advise on intellectual property matters involving patents, trademarks, trade secrets, licensing, open-source software, product development, and commercial transactions. Draft and negotiate IP-related agreements, support M&A due diligence, review marketing materials for compliance, and counsel cross-functional teams on strategic IP risks and opportunities.

Leads MAU analytics and data science, managing decision scientists and data scientists while setting quality standards. Owns MAU driver modeling, forecasting, causal analysis, experimentation, and exploratory work supporting growth strategy. Establishes consistent analytical practices, partners with revenue, product, engineering, and data engineering leaders, and embeds the team in roadmap planning. Promotes AI-native workflows through coding agents, automation, and analytical tools while coaching team members into strategic advisors.

Owner of Life360's unified organic discovery strategy across SEO, AEO/GEO, and ASO. Lead content strategy, site information architecture, technical SEO, structured data/AEO optimization, AI citation growth, regional localization, off-page authority, and performance reporting. Manage a content strategist and external agencies and partner with Engineering, Product, Marketing, and PR to execute technical and editorial initiatives that drive organic traffic and conversions.

Design, implement, and own a reusable on-device ML inference platform for resource-constrained devices. Integrate inference into RTOS firmware, develop drivers and DMA paths, debug on real hardware, train and optimize models for microcontroller-class hardware, and ship features to production while raising team expertise and using AI-assisted tooling.

Design, build, and maintain scalable distributed data pipelines and a secure data lakehouse for streaming and batch processing to support real-time analytics, ML, and experimentation. Automate, test, and harden workflows, architect logical and physical data models, build ML model features, and collaborate with product, analytics, and data science teams to turn data into value.