AI/ML Engineer
hace 2 semanas
AI/ML Engineer - Web Data Quality - Remote At Zyte, we eat data for breakfast and you can eat your breakfast anywhere and work for Zyte. Founded in 2010, we are a globally distributed team of over 250 Zytans working from more than 28 countries who are on a mission to enable our customers to extract the data they need to continue to innovate and grow their businesses. We believe that all businesses deserve a smooth pathway to data. For more than a decade, Zyte has led the way in building powerful, easy‑to‑use tools to collect, format, and deliver web data, quickly, dependably, and at scale. Today, over 3,000 companies and 1 million developers rely on our tools and services to get the data they need from the web. Data QA is an important function within Zyte. The Data QA team works to ensure that the quality and usability of the data scraped by our web scrapers meets and exceeds the expectations of our enterprise clients. Roles & Responsibilities Design and implement AI‑driven quality checks: build models to detect anomalies, identify schema drift, and classify data errors in real time Automate and scale QA: replace manual and rule‑based validation with ML‑powered solutions that continuously improve Leverage GenAI for validation: use embedding models, LLMs, and prompt‑driven pipelines to perform semantic checks on scraped data Develop monitoring & alerting pipelines: quantify data quality via KPIs, dashboards, and automated reports for stakeholders Experiment & innovate: research and prototype new AI techniques for QA, e.g. using embeddings, synthetic data, and reinforcement learning to stress‑test scrapers Collaborate cross‑functionally: work with developers, product managers, and account teams to integrate AI‑based QA into production workflows Communicate insights: present findings with clear visualizations, metrics, and evidence‑based recommendations to technical and non‑technical audiences Requirements Proficiency in Python & PyData stack (NumPy, pandas, scikit‑learn, PyTorch/TensorFlow preferred) 3+ years in a data science, applied ML, or data engineering role (ideally with exposure to QA or data validation at scale) Hands‑on experience with GenAI tools: LLM APIs (OpenAI, Anthropic, Google), prompt engineering, cost/token optimization Strong ML fundamentals: anomaly detection, classification, clustering, embeddings, evaluation metrics Experience with big data frameworks (Spark, BigQuery, or similar) Ability to work with very large datasets (millions+ of records) Version control skills (GitHub/Bitbucket) Excellent communication in English, both technical and non‑technical Desired Skills Prior experience in data quality automation or web data QA Familiarity with LangChain, MCP, Marvin, or similar orchestration frameworks Experience building QA dashboards or visualization layers Background in statistics or applied mathematics Previous remote/distributed work experience Benefits Become part of a self‑motivated, progressive, multi‑cultural team Have the freedom and flexibility to work from where you do your best work Attend conferences and meet with team members from across the globe Work with cutting‑edge open source technologies and tools Seniority Level Mid‑Senior level Employment Type Full‑time Job Function Other Industries IT Services and IT Consulting #J-18808-Ljbffr
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Senior ML Engineer
hace 5 días
Municipio de Cañada de Gómez, Argentina MURAL A tiempo completoA leading technology employer in Argentina seeks a Machine Learning Engineer to design and build generative AI features and scalable data pipelines. The ideal candidate will have over 5 years of experience in deep learning, proficiency in Python and modern ML toolchains, and a passion for AI innovation. This is a remote-first position offering great growth...
