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Jobs · Information Technology · California

Advanced Data Science Associate Consultant - Generative AI and Machine Learning

ZS · South San Francisco, CA · 4 wk ago
HybridInformation TechnologyFull-time

About the role

ZS is seeking a Data Scientist (Associate Consultant) with expertise in both Generative AI and traditional machine learning to join our dynamic team. This is a hands-on role that requires a strong foundation in ML theory, advanced skills in GenAI application development, and a practical understanding of deploying models.

Responsibilities

  • Design, build, and deploy advanced machine learning and GenAI models to solve key business problems.
  • Architect and develop complex, stateful multi-agent systems and workflows using modern agentic frameworks like LangGraph.
  • Develop and productionize sophisticated AI systems, including fine-tuning open-source LLMs, building advanced Retrieval-Augmented Generation (RAG) pipelines, and advanced prompt engineering development.
  • Lead the research, experimentation, and implementation of novel GenAI techniques to solve complex business problems, pushing the boundaries of what is possible.
  • Lead the end-to-end lifecycle of data science projects, from initial conception and data analysis to model deployment and in-production monitoring.
  • Ensure the operational viability of deployed models by implementing robust monitoring for performance and data drift.
  • Provide guidance and mentorship to Associate team members.

Requirements

  • A PhD Degree in Computer Science, Statistics, or a relevant field or a master’s degree with 3-5 years of relevant post-collegiate work experience.
  • Demonstrated experience in designing, building, and deploying Generative AI applications, with hands-on expertise in techniques such as fine-tuning, prompt engineering, Agentic systems, Retrieval-Augmented Generation (RAG), and working with vector databases.
  • Strong proficiency in Python and core data science libraries (e.g., pandas, scikit-learn).
  • Experience with deep learning frameworks such as PyTorch or TensorFlow.
  • Prior leadership experience from a relevant position.
  • Fluency in English.

Additional Skills

  • Deep, hands-on experience building multi-agent systems with frameworks like LangChain, LangGraph, or similar Agent Development Kits (ADKs).
  • Deep experience with GenAI frameworks like LangChain, LlamaIndex, Hugging Face ecosystem & familiarity to MCP tools.
  • Experience with model quantization, inference optimization, and other techniques for the efficient deployment of large models.
  • Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services.

Qualifications

  • PhD Degree in Computer Science, Statistics, or a relevant field or a master’s degree with 3-5 years of relevant post-collegiate work experience.
  • Hands-on experience in designing, building, and deploying Generative AI applications, with expertise in techniques such as fine-tuning, prompt engineering, Agentic systems, Retrieval-Augmented Generation (RAG), and working with vector databases.
  • Strong proficiency in Python and core data science libraries (e.g., pandas, scikit-learn).
  • Experience with deep learning frameworks such as PyTorch or TensorFlow.
  • Prior leadership experience from a relevant position.
  • Fluency in English.
  • Deep, hands-on experience building multi-agent systems with frameworks like LangChain, LangGraph, or similar Agent Development Kits (ADKs).
  • Deep experience with GenAI frameworks like LangChain, LlamaIndex, Hugging Face ecosystem & familiarity to MCP tools.
  • Experience with model quantization, inference optimization, and other techniques for the efficient deployment of large models.
  • Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services.

Skills

  • Advanced skills in GenAI application development.
  • Practical understanding of deploying models.
  • Classical machine learning techniques (e.g., predictive modeling, time-series analysis, classification).
  • Collaboration with cross-functional teams, including engineers, product managers, and domain experts.
  • Model deployment and in-production monitoring.
  • Multi-agent systems and workflows using modern agentic frameworks like LangGraph.
  • Research, experimentation, and implementation of novel GenAI techniques.
  • End-to-end lifecycle of data science projects.
  • Operational viability of deployed models by implementing robust monitoring for performance and data drift.
  • Guidance and mentorship to Associate team members.

Benefits

At ZS, your growth matters. We offer a comprehensive total rewards package that supports your health and well-being, financial future, time away, and professional development. With robust skills-building programs, multiple career progression paths, internal mobility, and a deeply collaborative culture, you’ll have the opportunity to do meaningful work, expand your capabilities, and thrive as part of a global community.

Pay

Competitive compensation and benefits package.

Schedule

Hybrid working model: We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections.

Travel

Travel is a requirement at ZS for client facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures.

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