Job description

Applied ML Scientist FTE, Fully Remote(Must reside in EST or CST timezone) Company Overview Our client is a market-leading enterprise operating a substantial national footprint. Driven by a mission of customer-first service and operational excellence, the organization leverages modern technology and data science to power high-impact business decisions at massive scale. Joining this team means contributing to a forward-thinking environment where practical AI solutions directly influence real-world customer and operational outcomes. Role Summary The Intersect Group is seeking an Applied ML Scientist to serve as a key individual contributor within our client’s AI and Data team. In this role, you will design, train, and deploy advanced machine learning models that address complex operational and business challenges across multiple business units and operational channels. You will translate ambiguous business problems into scalable statistical models, evaluate their performance against real-world metrics, and ensure seamless handoffs to engineering teams for production deployment. This position focuses heavily on developing traditional machine learning models (such as XGBoost) and cloud-based AI solutions, with additional opportunities to drive computer vision initiatives. Key Responsibilities Design & Model Development: Build, train, and validate supervised and unsupervised machine learning models using appropriate algorithms and rigorous cross-validation techniques. Feature Engineering & EDA: Conduct comprehensive exploratory data analysis, data cleaning, and feature engineering on complex tabular datasets using SQL and Python. Cloud Architecture & Deployment: Leverage Google Cloud Platform (GCP) and Vertex AI to build end-to-end ML solutions optimized for production environments. Cross-Functional Collaboration: Work alongside ML Product Managers and ML Systems Engineers to align models with business objectives and meet latency, memory, and scalability standards. Documentation & Governance: Maintain detailed model registries, technical runbooks, architecture diagrams, and performance benchmarks to ensure reproducible workflows. Applied Vision & Innovation: Explore and apply computer vision frameworks (e.g., PyTorch, OpenCV, YOLO, Vision Transformers) to improve operational execution, object detection, and visual tracking where applicable. Key Requirements Experience & Education: 2–4+ years of hands-on experience in applied machine learning or data science roles in production environments; a PhD in Data Science, Computer Science, Statistics, or a related quantitative field is preferred. Cloud Platform Mastery: Demonstrated expertise building and deploying machine learning solutions specifically on GCP Cloud (Vertex AI). Core ML Expertise: Deep proficiency in Python and traditional, tree-based machine learning models, with extensive experience in XGBoost, LightGBM, and scikit-learn. Data & Tooling Stack: Advanced proficiency with SQL, pandas, NumPy, and experiment tracking tools such as MLflow or Weights & Biases. Domain Knowledge: Strong background working with tabular data in retail, supply chain, e-commerce, or consumer analytics contexts. Computer Vision Skills (Bonus): Hands-on experience developing vision models using CNNs, Vision Transformers, YOLO, or Detectron2 for object detection or OCR. Problem-Solving & Communication: Proven ability to navigate ambiguous problem spaces, articulate the technical reasoning behind model choices, and communicate complex trade-offs to non-technical stakeholders. Ready to Take the Next Step? If you are an experienced ML Scientist ready to make an impact on a massive scale, we want to hear from you! Please apply today by submitting your current resume and contact details to The Intersect Group.

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