Negotiable
Undetermined
Remote
Remote
Summary: The Senior AI/ML Scientist role focuses on designing, building, and scaling machine learning systems to enhance personalization and business decision-making. This position requires expertise in advanced machine learning techniques, statistical modeling, and the integration of Generative and Agentic AI. The successful candidate will lead research efforts and mentor junior team members while deploying solutions on Google Cloud Platform. A PhD and extensive experience in the field are essential for this long-term contract position.
Key Responsibilities:
- Design, develop, and deploy production-grade propensity models and recommendation systems
- Lead applied research and statistical analysis to support business strategy and experimentation
- Build, train, and deploy ML models on Google Cloud Platform (Vertex AI, BigQuery ML, Dataflow, Cloud Run)
- Integrate Generative AI and Agentic AI capabilities into ML workflows and products
- Design feature stores, training pipelines, and model monitoring frameworks
- Translate business problems into scalable machine learning solutions
- Mentor junior team members and contribute to MLOps best practices
Key Skills:
- Machine Learning & Statistical Modeling
- Google Cloud Platform (Vertex AI, BigQuery)
- Generative AI & Agentic AI
- Python (TensorFlow / PyTorch / Scikit-learn)
- Recommendation Systems & Propensity Modeling
Salary (Rate): undetermined
City: undetermined
Country: United States
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: Senior
Industry: IT
Location: Remote (United States)
Type: Long Term Contract
Experience: 10+ Years
Education: PhD Required
- Design, develop, and deploy production-grade propensity models and recommendation systems
- Lead applied research and statistical analysis to support business strategy and experimentation
- Build, train, and deploy ML models on Google Cloud Platform (Vertex AI, BigQuery ML, Dataflow, Cloud Run)
- Integrate Generative AI and Agentic AI capabilities into ML workflows and products
- Design feature stores, training pipelines, and model monitoring frameworks
- Translate business problems into scalable machine learning solutions
- Mentor junior team members and contribute to MLOps best practices
- Machine Learning & Statistical Modeling
- Google Cloud Platform (Vertex AI, BigQuery)
- Generative AI & Agentic AI
- Python (TensorFlow / PyTorch / Scikit-learn)
- Recommendation Systems & Propensity Modeling
- PhD in Computer Science, Statistics, Machine Learning, Applied Mathematics, or a related quantitative field
- 5+ years of industry experience building and deploying ML models in production
- Expertise in causal inference, A/B testing, and experimental design
- Strong experience with LLMs, RAG, prompt engineering, and agent frameworks
- Must be authorized to work in the United States or Canada