Own end-to-end matching and ranking systems for out-of-home advertising: design candidate generation and re-ranking models, build and manage data warehouse and pipelines, implement evaluation and monitoring, publish low-latency ranking APIs, and maintain model observability and retraining workflows.
About Onescreen
Onescreen is the modern platform for out-of-home advertising — making it easier for brands and agencies to plan, buy, and measure OOH campaigns across thousands of vendors and formats. We move fast, operate lean, and hold ourselves to a high standard on every campaign we run.
About the role
You'll be the founding ML engineer who owns our matching algorithms from exploration through production and the data platform that feeds them. You'll design and ship the models that rank OOH inventory against advertiser personas, markets, and dayparts. You'll own our data warehouse shape and the pipelines that fill it. You'll publish the ranking and matching APIs that downstream products, agents, and automation surfaces consume.
What you'll do
- Design and ship matching and ranking models for OOH inventory: candidate generation, re-ranking, geospatial-aware scoring.
- Own the data warehouse layer end to end: staging, marts, feature pipelines, freshness, lineage.
- Stand up offline and online evaluation infrastructure — measure the gap between them, don't assume it.
- Publish ranking and matching APIs for product surfaces, with latency and quality SLOs.
- Instrument model monitoring: drift detection, prediction distribution, feature freshness, retraining triggers.
Qualifications
The hard requirement: you have owned a production ranking, matching, or recommendation system end-to-end. You chose the model, designed the features, made the evaluation methodology calls, and were on the hook when it drifted. We care about that ownership scope more than years on a résumé — title and compensation are scaled to your demonstrated expertise.
Beyond that:
- Strong production Python (NumPy, Pandas, FastAPI, SQLAlchemy).
- Strong SQL and modern data warehouse experience (BigQuery preferred).
- Real ranking and matching modeling fluency — learning-to-rank, retrieval and re-rank patterns, not just classification.
- Evaluation methodology rigor: holdouts, leakage prevention, online vs. offline gap measurement.
- Comfort owning the data pipeline as well as the model.
- Bias toward shipping. Clear writer. Self-directed.
Nice to have
- Geospatial data experience (H3, PostGIS, GeoPandas)
- Mobility or location data experience
- Embedding-based retrieval (pgvector, FAISS, vector databases)
- Bandits, contextual bandits, or online learning
- A/B testing infrastructure design
- Causal inference
- dbt
- Ad-tech or OOH domain familiarity
Onescreen Boston, Massachusetts, USA Office
Boston, MA, United States
Similar Jobs
Artificial Intelligence • Machine Learning • Software • Analytics
Founding Engineer responsible for building FilmoreAI’s production AI and data platform for construction equipment dealers. The role covers agent infrastructure, model routing, LLM extraction and reasoning, canonical data modeling, entity resolution, Python data pipelines, Azure cloud orchestration, evaluation, observability, and safe human-approved write-back. The engineer will work independently in an ambiguous startup environment and use agentic development tools to ship reliable systems with strong cost, latency, accuracy, and operational guardrails.
Top Skills:
AirbyteAzureAzure Blob StorageAzure Container AppsAzure Database For PostgresqlAzure Synapse AnalyticsClaudeCrm ApisDatabricksDatadogDbtFastapiGeminiGithub ActionsGptLangchainLanggraphLangsmithMcpMicrosoft FabricPgvectorPlaywrightPostgresPublic ApisPydantic AiPythonSecret ManagerSQLTemporal CloudTerraformTwilio
Artificial Intelligence • Cloud • Consumer Web • Productivity • Software • App development • Data Privacy
Own DocSend customer-facing product experiences from discovery through launch and iteration. Define product strategy, prioritize customer problems, guide Engineering and Design, evaluate quantitative and qualitative insights, establish success measures, and drive foundational improvements, AI-powered workflows, and multi-product experiences across Dropbox and DocSend.
Top Skills:
AIAutomationSaaS
Artificial Intelligence • Fintech • Hardware • Information Technology • Sales • Software • Transportation
Own full-cycle recruiting for sales and business-critical roles, from intake through offer and closing. Partner with hiring managers and senior leaders on candidate profiles, search strategy, market conditions, interviews, and offers. Build passive-candidate pipelines through sourcing, networking, referrals, and market mapping. Use recruiting metrics and ATS data to identify bottlenecks and improve processes while delivering an inclusive, consistent candidate experience.
Top Skills:
Applicant Tracking System (Ats)Ats Data AnalyticsRecruiting Metrics
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
