Top Tech Jobs & Startup Jobs in Boston, MA

Lead Platform Systems engineering: define technical strategy, drive AI stack modernization, improve reliability, capacity, cost efficiency, and developer productivity; hire and develop engineers; deploy GenAI tooling; and coordinate cross-functional execution across AIMS and infrastructure teams.

Lead design and execution of a modernized, Python-native AI/ML platform for AIMS: define architecture, drive migration, build migration tooling, ensure scalability, observability, cost optimization, and reliability, prototype GenAI operational tooling, and set org-wide technical standards.

Lead the end-to-end cloud gaming product for connected TVs, own the mobile-as-controller roadmap, bridge viewing and playing experiences, optimize QoE (latency, input lag, video fidelity), design 10-foot UI flows, and coordinate cross-functional execution with game studios, platform and mobile engineering, and data science.

Build and deliver consumer-facing TV application features and core client/UI capabilities. Design, architect, debug, test, and document performant, maintainable code; partner with designers, product, and cross-functional teams to componentize abstractions and improve developer experience and stability for large-scale systems.

Build and operate scalable, highly available ML/LLM serving and compute infrastructure. Own long-term platform vision, deliver zero-to-one projects, partner cross-functionally, optimize performance and capacity, and support production ML models at scale.

Design, build, and maintain tools and services for Active Directory and cloud identity platforms. Implement security policies and access controls, collaborate on Azure and Google Workspace deployments, automate integrations via APIs and CI/CD, maintain runbooks, participate in on-call rotation, and support AWS infrastructure for production systems.

Design, develop, and scale software systems for machine learning algorithms powering personalization. Collaborate with researchers and product teams to implement production-ready, distributed solutions, enable offline experiments and A/B tests, and improve engineering practices and systems across teams.

Design, productionize, and deploy machine learning forecasting models for ad inventory and campaign performance in low-latency, real-time advertising environments. Build scalable simulation, budgeting, and pacing systems; collaborate with cross-functional teams to deploy models at scale and optimize ad monetization.

Lead content design for acquisition across Mobile, Web, and TV: write persuasive, on‑brand copy, develop scalable language systems, collaborate with product/design/engineering/research, and design/run experiments from ideation through execution.

Build and own internal data visualization web applications for content reporting. Partner with product, data scientists, and R&D to integrate multiple data sources, design intuitive charts, iterate on UX based on feedback, and surface metrics and predictive analytics for business stakeholders.