Quantiphi

Sr. Machine Learning Engineer (Data Science)

Vaga remota de Machine Learning Engineering com fit claro de localização do candidato.

Publicada19 de jul. de 2026

Países elegíveis1 país aceito

Sinal de senioridadeSenior

Modelo de trabalhoRemoto

Locais aceitos para candidatos

Estados Unidos

AWS GCP LLM Python Snowflake SQL

Resumo da vaga

Sr. Machine Learning Engineer (Data Science)

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

About Quantiphi:

21 Google Cloud Partner of the Year awards in the past 10 years
3 AWS AI/ML Partner of the Year awards
3 NVIDIA Partner of the Year awards
3 Snowflake Partner of the Year awards
Rated Leaders by Gartner, Forrester, IDC, ISG, Everest Group and other leading analyst firms

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.

Required Qualifications

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.

Preferred Qualifications

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.

What’s in it for YOU at Quantiphi?

Join one of the world’s fastest-growing AI-first digital engineering companies and make a real impact at scale.
Lead and collaborate with a high-energy team of talented, driven individuals solving complex, meaningful challenges.
Work with Fortune 500 companies and disruptive innovators in a research-driven environment with 60+ patents.
Stay ahead of the curve by gaining hands-on experience with cutting-edge AI, ML, data, and cloud technologies while continuously upskilling.

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