Jobs at tvScientific

Lead quality efforts for a web platform and APIs by designing/executing manual and automated tests, building test suites (UI, API, integration), integrating tests into CI/CD, investigating failures, and driving cross-functional quality improvements.

Design and build simulation environments modeling CTV auction mechanics, bidding strategies, and campaign outcomes. Create counterfactual frameworks, AI agents for experimentation, and use simulation to validate ML deployments. Define technical direction and mentor engineers.

Manage a portfolio of client accounts for a CTV advertising platform: launch and optimize campaigns, develop strategic account plans, drive revenue through upsell/cross-sell, analyze performance metrics, collaborate with internal teams, mentor junior staff, and use AI tools to accelerate optimizations and reporting.

Lead strategic relationships for gaming clients, launch and optimize programmatic CTV campaigns to meet CPA/CPI/ROAS targets, develop account plans and QBRs, drive upsell and retention, analyze funnels and metrics, collaborate with sales/product/AdOps, mentor junior staff, and use AI to accelerate campaign optimization.

Lead product vision and execution for CTV creative tooling: asset ingestion, generation, variant production, and creative-aware optimization. Build AI-driven tools to convert brand assets into TV-ready commercials, integrate creative signals into prediction/optimization models, partner with commercial teams for adoption, and represent the company externally.

Lead design and implementation of identity resolution and data governance systems. Build batch and streaming pipelines, APIs, and services to ingest, normalize, link, and version identity data. Ensure auditable matching, data lineage, quality checks, schema enforcement, access controls, and privacy-by-design. Collaborate cross-functionally with product, analytics, legal, privacy, and security teams and create documentation, monitoring, and runbooks.

Design and operate ML training and serving infrastructure, build a Kubernetes+Ray backend, improve developer experience and observability, mentor engineers, and ensure reliable, secure deployments for low-latency, high-performance systems.

Act as the technical lead during sales: scope integrations, recommend measurement/attribution solutions, troubleshoot implementation issues, translate technical concepts for clients, and liaise with Product/Engineering/Customer Success. Document best practices and use AI tools to accelerate discovery, troubleshooting, and documentation to ensure successful onboarding and long-term client outcomes.

Design and implement scalable data infrastructure and pipelines on AWS using Spark and Scala. Build fault-tolerant batch and streaming workflows, optimize storage formats and engines, enforce automated data quality checks, and collaborate with Data Science and Product teams to deliver reliable data assets and APIs.

Design, build, and scale backend contract and billing services supporting CPA and CPM models. Implement contract lifecycle, rate management, APIs, and integrations with finance. Ensure data integrity, auditability, reliability, observability, and performance. Lead technical design, mentor engineers, and collaborate with Product, Finance, and Data teams.

Design, build, and optimize scalable data infrastructure and pipelines on AWS using Spark/Scala. Store and model data in appropriate engines and formats, implement knowledge graphs accessible via batch jobs and APIs, enforce automated data quality checks, and collaborate with Data Science and Product teams to deliver performant, cost-effective data services.

Build and harden low-latency, high-throughput ML platform infrastructure. Design storage, indexing, streaming, backpressure, failure handling, and observability. Scale decisioning, improve developer experience for data scientists, manage Kubernetes deployments, and collaborate with SRE, data infra, and engineering to ensure reliable, debuggable production systems.

Design and implement CTV advertising simulations and AI-driven tooling. Build auction, bidding, and counterfactual frameworks; develop agentic AI for strategy exploration; validate ML models offline; define simulation and AI infrastructure; mentor engineers and drive end-to-end delivery of simulation and deployment systems.

Own analytics projects end-to-end: write production Python code, design and analyze experiments to optimize CTV ad campaigns, build reporting and analytics tools, and translate insights into the Data Science product to support stakeholders and improve campaign performance.

Design, build, and scale backend services for contract lifecycle and billing systems (CPA and CPM models). Develop APIs, ensure data integrity, auditability, reliability, and performance. Partner with Product, Finance, and Data teams, lead technical design, mentor engineers, and improve observability and error handling across contract workflows.