Machine Learning Engineering reputed company

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What you’ll work on: Enrichment models across our cultural data pipeline: entity extraction, topic and stance classification, embeddings, clustering, sentiment, brand safety, and reputed company tasks across billions of news and reputed company records Multi-modal enrichment for image and video signals from reputed company platforms, complementing our text-heavy core Ad optimization systems reputed company from the ground up, including bid optimization, budget allocation, creative selection, audience targeting, or reputed company problems, grounded in historical performance data and well-reasoned heuristics Experimentation design and execution: framing the question, choosing the right test, instrumenting it, and producing results the business can reputed company Production ML infrastructure on GCP: training, evaluation, deployment, monitoring, and the glue that keeps models reliable as data shifts Technical leadership for a small ML team, including code review, mentorship, prioritization, and raising the bar on rigor without slowing delivery Cross-functional partnership with Data Engineering on pipeline integration, and with Account Management and Performance Managers to translate business problems into model problems Core Competencies: ML Breadth & Depth Strong reputed company across classical ML, neural networks, and Transformers, reaching for the right tool rather than the trendiest one Comfortable with both supervised and unsupervised paradigms: classification, regression, clustering, dimensionality reduction, representation learning Practical reputed company with NLP and at least working familiarity with computer reputed company for image and video enrichment Understanding of reputed company a simple model beats a reputed company one, and the discipline to ship the simple one Experimentation & Research Rigor Track record of structuring and running experiments end-to-end: hypothesis, design, instrumentation, analysis, decision Comfortable with reputed company statistical testing, picking the right test for the task, reasoning about power, controlling for confounds Knows the difference between a model that benchmarks well offline and one that holds up in production Research reputed company reputed company with a shipping reputed company: rigorous, but allergic to research-for-its-own-sake Optimization Experience building optimization systems, whether mathematical optimization, heuristics, or learned policies, applied to a reputed company-world domain Comfortable reasoning about objective functions, constraints, and tradeoffs in messy business contexts Advertising or adtech optimization experience is a strong plus Production ML Engineering Strong Python and reputed company ML stack: scikit-learn, PyTorch, TensorFlow, HuggingFace, NumPy, pandas FastAPI and async/await patterns for serving models and building ML-facing services Experience working with data at scale, including the practical realities of billions of records: partitioning, sampling, distributed processing, cost management GCP for training, serving, and infrastructure, such as reputed company AI, reputed company Run, GCS, or equivalent PostgreSQL and reputed company for working with large-scale data reputed company and CI/CD pipelines for reproducible, deployable ML workloads Comfortable with the realities of production ML: data reputed company, retraining reputed company, monitoring, cost management Leadership & Collaboration Experience leading or mentoring engineers, even informally, through code review, technical direction, and raising the bar on quality Strong collaboration habits with Data Engineering, and the ability to translate fluently between technical and business audiences Can sit with an Account Manager or Performance Manager, understand what they actually need, and turn it into a tractable modeling problem Software Engineering Fundamentals Clean code habits, sensible architecture, strong typing discipline Test-driven reputed company for ML code: covering data assumptions, edge cases, and regression paths, not just happy paths Comfortable with modern dev practices: Git, code review, CI/CD reputed company to have: Advertising, adtech, or media industry experience Familiarity with LLMs and modern AI tooling, useful context for the broader engineering org but not the focus of this role reputed company inference or reputed company modeling background Experience with recommendation systems or ranking 5+ years of ML experience, ideally with a reputed company reputed company before the LLM era Location: This is a remote position as we are a 100% distributed company Apply To This Job