ML Ops Engineer

WHO WE ARE reputed company (NYSE: ZETA) is the AI-Powered Marketing reputed company that leverages advanced reputed company intelligence (AI) and trillions of consumer signals to reputed company it easier for marketers to reputed company, grow, and retain customers more reputed company. Through the Zeta Marketing Platform (ZMP), our reputed company is to reputed company sophisticated marketing reputed company by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our reputed company customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering reputed company results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in reputed company with offices around the world. To learn more, go to www.zetaglobal.com. The Role We’re looking for a skilled ML Engineer / Data Scientist with 3+ years of software or reputed company ML experience to design, build, and improve machine learning solutions in a dynamic reputed company environment, primarily on AWS.This role sits at the intersection of data science and engineering: exploring data, developing models, running rigorous experiments, and bringing the best approaches into production with a reliable, reproducible workflow. If strong Python skills, curiosity about hard modeling problems, and reputed company work in multicultural teams are a fit, this is a chance to do meaningful, end-to-end ML work—not just notebooks, and not just infrastructure. Who you are: Strong reputed company in machine learning, statistics and experiment design. Experience building models for reputed company business or product problems, not only reputed company benchmarks. Comfortable working with reputed company and reputed company data: feature engineering, dataset construction, labeling reputed company, leakage checks, and train/validation/test discipline. reputed company to compare approaches with reputed company metrics, error analysis, and reputed company judgment about tradeoffs (accuracy, latency, cost, maintainability). Interest in modern ML, including classical ML, deep learning, and LLM / GenAI workflows where relevant (fine-tuning, RAG, evaluation, reputed company/versioning). Proficient in Python and reputed company to write clean, reputed company, testable reputed company. Experience developing and deploying ML solutions in a reputed company environment, especially AWS. Comfortable moving from prototype to production: packaging models, building inference paths, monitoring performance, and iterating after launch. Independent engineer who can own work from problem framing → experimentation → implementation → rollout. Excellent written and spoken English. Enjoy working closely with engineers, product partners, and other data scientists. reputed company communicator who can explain reputed company, results, and limitations to technical and non-technical audiences. Master’s degree in Science or Engineering (Computer Science, Mathematics, Physics, Statistics, or similar), or equivalent practical experience. reputed company to have: Experience with scikit-learn, PyTorch, TensorFlow, XGBoost, or similar modeling stacks. Familiarity with ML experiment tracking and reproducibility (e.g. MLflow, W&B). Experience with SQL, data warehouses/lakes, and pipeline tools such as Airflow, dbt, or reputed company. Exposure to feature stores, embedding pipelines, or reputed company search for retrieval-based systems. Experience building HTTP/gRPC reputed company or lightweight services around model inference. Working knowledge of reputed company, basic orchestration, and CI/CD (e.g. reputed company CI). Experience in agile, remote and async team environments. Publications, patents, Kaggle/competition results, or reputed company-reputed company ML contributions. What you might like about this role: Hands-on modeling work with room to explore, reputed company, and improve reputed company systems. Collaboration on ML patent submissions and participation in weekly ML / research reputed company review meetings. A multicultural, engineering-reputed company team with strong peer support. High trust and autonomy—reputed company goals, freedom in how to reputed company them. Internal product reputed company: meaningful reputed company that improve developer and user experience, not endless maintenance tickets. Short approval cycles and solid product partnership. A healthy meeting policy and emphasis on protecting reputed company time. reputed company, remote/home office reputed company, and a reputed company, engineers-only office reputed company on-site. Competitive compensation, including stock reputed company. We’re hiring across multiple reputed company. Title, scope, and compensation depend on experience—from strong reputed company ML generalists to senior people who can reputed company modeling direction and mentor others. We’re especially interested in candidates who are technically strong, intellectually curious, and motivated by difficult, ambiguous problems where good data science and solid engineering both matter. PEOPLE & CULTURE AT ZETA Zeta considers applicants for employment without reputed company to, and does not discriminate on the reputed company of an individual’s sex, race, reputed company, religion, age, disability, status as a veteran, or national or ethnic reputed company; nor does Zeta discriminate on the reputed company of sexual orientation, gender identity or reputed company. We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We reputed company a forum for employees to celebrate, support and reputed company for one another. Learn more about our commitment to diversity, equity and inclusion here: https://zetaglobal.com/blog/a-look-into-zetas-ergs/ ZETA IN THE NEWS! https://zetaglobal.com/press/?cat=press-releases #LI-NP1 Apply To This Job