Machine Learning Engineer Why Join This Opportunity? This organization is at the forefront of leveraging data intelligence to influence consumer behavior at the point of purchase. Through advanced AI solutions, they support leading global brands across industries such as Consumer Packaged Goods, Health & Well-Being, Technology, and Retail—helping optimize packaging, enhance engagement, and drive sales. You'll be joining a fast-paced, highly collaborative AI and engineering team where your work directly contributes to production-grade systems deployed at scale. What You'll Do Data Quality & Pipeline Audit and improve training data pipelines: identify problematic samples, resolve mislabeling, refine train/test splits, and detect data leakage Build robust, reproducible data workflows Model Evaluation Develop and run reproducible evaluation workflows across regions, KPIs, and categories Create qualitative assessment frameworks that go beyond aggregate metrics Experimentation Execute ML experiments including new data splits, augmentation strategies, encoders, and hyperparameter tuning Apply modern computer vision and multimodal techniques where relevant to real-world problems Productionization Integrate validated experiments into production pipelines Standardize research workflows (e.g., saliency maps, visualization tools) for repeatability Ensure proper testing, documentation, and deployment without breaking existing systems Infrastructure Support ML training infrastructure on Azure (job execution, checkpointing, debugging, reproducibility) Ad Hoc Data Analysis Perform SQL-based data extraction and analysis Investigate model performance across segments and deliver actionable insights to stakeholders What You'll Bring Essential Qualifications 3–5 years of experience in applied ML or ML engineering, ideally with computer vision or multimodal models Strong software engineering skills with production-grade Python (not just notebooks) Experience working in structured codebases and shipping via PRs Proficiency in Python ML stack (pandas/polars, PyArrow, scikit-learn, NumPy) Strong SQL skills and comfort with data analysis Hands-on experience with PyTorch or similar deep learning frameworks Experience with Azure ML or equivalent cloud platforms Familiarity with AI-assisted development tools (e.g., Copilot, Cursor, Claude Code) Strong written communication and documentation skills Preferred Qualifications Experience with transfer learning and vision encoders (e.g., CLIP, SigLIP) Familiarity with tools like PyTorch Lightning, Optuna, MLflow Experience with CI/CD pipelines and containerization Exposure to Databricks, Azure Blob Storage, or similar platforms Ability to read and apply ML research in practical environments Background in consumer research or behavioral science is a plus Working Conditions Employment Type: Full-time Work Setup: Hybrid (Makati) Schedule: Night shift What's in It for You Work on impactful, production-level AI systems used by global brands Strong mentorship and career growth opportunities Access to cutting-edge tools and modern ML infrastructure Exposure to large-scale, real-world datasets Clear progression path toward ownership and technical leadership
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