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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Machine Learning Engineer (Data Science) - **Company:** Quantiphi, Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $140,000.0 - $193,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Airflow, Data Analysis, Big Data, BigQuery, Cloud Storage, Information Engineering, Monitoring of Systems, Statistical Hypothesis Testing, Inventory Management Software, Python (Programming Language), Machine Learning, NumPy, Tensorflow, SQL Databases, Systems Integration, Workflow Management Systems, Google Cloud, Cloud Platform System, Feature Engineering, Pytorch, Prophet, Large Language Models, Prompt Engineering, Deep Learning, Pandas, Scikit Learn, Information Technology, Statistics Packages, Google Cloud Functions, Machine Learning Operations, Virtual Agents, Software Version Control, Data Pipelines - **Published:** July 17, 2026 - **Apply:** https://quantiphi.wd1.myworkdayjobs.com/Careers_at_Quantiphi/job/USA---Remote/Sr-Machine-Learning-Engineer--Data-Science-_JR7446-1 ## About the Role * 6+ years of experience in machine learning engineering and data science, with a strong portfolio of deployed forecasting or predictive models. * Proficiency in Python (Pandas, NumPy, scikit-learn, statsmodels) and at least one deep learning framework (TensorFlow, PyTorch, or JAX). * Hands-on experience with GCP ML stack: Vertex AI (Training, Prediction, Pipelines), BigQuery, Cloud Functions, Cloud Storage, and Pub/Sub. * Strong foundation in statistics, probability, and time-series analysis (ARIMA, Prophet, exponential smoothing, state-space models). * Experience building or integrating with AI agent frameworks (LangChain, LlamaIndex, Vertex AI Agents, or similar agentic orchestration tools). * Proficiency in SQL for complex analytical queries on large-scale data warehouses. * Experience with experiment tracking and model management tools (MLflow, Vertex AI Experiments, Weights & Biases). * Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field., * Google Cloud Professional Machine Learning Engineer or Professional Data Engineer certification. * Experience in supply chain, distribution, or logistics domain with demand forecasting use cases. * Familiarity with LLM fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) patterns for enterprise AI agents. * Prior consulting or professional services experience with client-facing delivery in an Agile environment. * Engagement Details ## Description Quantiphi is seeking a Sr. Machine Learning Engineer with strong data science expertise to support an AI agents engagement with a leading global technology distribution and solutions company. This role will focus on developing intelligent forecasting models and quotation automation agents on Google Cloud Platform (GCP). The ideal candidate combines deep statistical modeling skills with production ML engineering to deliver data-driven agentic AI solutions that drive operational efficiency across the client's distribution ecosystem. Key Responsibilities * Design, develop, and deploy forecasting models (time-series, demand forecasting, regression-based) for product demand, pricing trends, and quotation accuracy using GCP-native services (Vertex AI, BigQuery ML). * Conduct exploratory data analysis (EDA), feature engineering, and hypothesis testing on large-scale distribution and supply chain datasets to surface actionable insights for AI agent decision logic. * Build AI agents for forecasting and quotation workflows using agentic frameworks (LangChain, Vertex AI Agents, CrewAI) with data-driven decision-making capabilities embedded in agent reasoning. * Develop and maintain production ML pipelines on Vertex AI Pipelines and Cloud Composer for model training, evaluation, deployment, and retraining automation. * Implement statistical experimentation frameworks (A/B testing, causal inference) to validate model improvements and measure business impact of forecasting agents. * Collaborate with data engineering teams to design feature stores and data pipelines in BigQuery and Cloud Storage that feed forecasting and quotation models. * Optimize model performance through hyperparameter tuning, cross-validation, ensemble methods, and model interpretability techniques (SHAP, LIME) for stakeholder transparency. * Integrate ML model outputs into agentic workflows, enabling agents to autonomously generate, validate, and refine quotations based on real-time market and inventory data. * Document model architectures, experiment results, and agent decision logic; present findings and recommendations to client stakeholders and Quantiphi leadership. * Contribute to MLOps best practices including model versioning, drift detection, monitoring dashboards, and automated alerting using Vertex AI Model Monitoring. ## Related Videos - [Architecting the Future: Leveraging AI, Cloud, and Data for Business Success](https://www.wearedevelopers.com/videos/1096-architecting-the-future-leveraging-ai-cloud-and-data-for-business-success) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Vectorize all the things! 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Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Prompt Engineering is a Job of the Past](https://www.wearedevelopers.com/magazine/342-prompt-engineering-is-a-job-of-the-past) - [The Prompt Engineer ✍️](https://www.wearedevelopers.com/magazine/216-the-prompt-engineer)