AI/ML Engineer - Web Data Quality (Remote)

Overview

This position is posted by Jobgether on behalf of Zyte. We are currently looking for an AI/ML Engineer - Web Data Quality in Argentina, Uruguay, Brazil, Portugal, or Croatia.

As an AI/ML Engineer focused on web data quality, you will play a critical role in ensuring that large-scale data extraction processes deliver highly accurate and usable data. You will leverage Python, machine learning, and AI techniques to design automated quality checks, detect anomalies, and validate data integrity in real time. This role offers the opportunity to innovate with cutting-edge GenAI tools and big data technologies while collaborating closely with cross-functional teams. You will contribute to improving processes, monitoring KPIs, and visualizing insights to ensure data excellence for enterprise clients. This position is ideal for someone passionate about AI, data quality, and building scalable solutions in a fully distributed and collaborative environment. Accountabilities

• Design and implement AI-driven data quality checks, including anomaly detection, schema drift identification, and error classification.
• Automate and scale QA processes to replace manual validation with ML-powered solutions.
• Leverage GenAI tools, embeddings, LLMs, and prompt-driven pipelines for semantic data validation.
• Develop monitoring and alerting pipelines, generating KPIs, dashboards, and automated reports for stakeholders.
• Research, prototype, and experiment with new AI techniques to stress-test data extraction and QA processes.
• Collaborate with developers, product managers, and account teams to integrate AI-based QA into production workflows.
• Communicate findings effectively to technical and non-technical audiences with clear visualizations and evidence-based recommendations.
• Proficiency in Python and the PyData stack (NumPy, pandas, scikit-learn; PyTorch/TensorFlow preferred).
• 3+ years of experience in data science, applied ML, or data engineering, ideally with exposure to QA or data validation at scale.
• Hands-on experience with GenAI tools, including LLM APIs (OpenAI, Anthropic, Google), prompt engineering, and cost/token optimization.
• Strong ML fundamentals: anomaly detection, classification, clustering, embeddings, and evaluation metrics.
• Experience with big data frameworks such as Spark, BigQuery, or similar.
• Ability to work with very large datasets (millions+ records).
• Version control skills (GitHub or Bitbucket).
• Excellent English communication skills for both technical and non-technical audiences.
• Desired: experience with data quality automation, LangChain or similar frameworks, QA dashboards, statistics/applied mathematics, and prior remote/distributed work.
• Work in a fully distributed, flexible, and multicultural environment.
• Freedom to work from your preferred location.
• Opportunities to attend conferences and collaborate with international team members.
• Exposure to cutting-edge open-source technologies and AI tools.
• Participate in a mission-driven, innovative, and collaborative team culture.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. It compares your profile to the job’s core requirements and past success factors to determine your match score. Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role. When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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