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Emergence AI

Orchestrates multi-agent AI for enterprise automation

Staff Applied Data Scientist - Agentic AI

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeIrvine, CA, USA

About the Job

Requirements

  • Significant experience building production machine learning or applied data science systems.
  • Strong Python skills and experience with modern machine learning and data science libraries.
  • Deep expertise in statistical modeling, machine learning, experimentation, and model evaluation.
  • Experience working with large, complex enterprise or operational datasets.
  • A track record of taking ambiguous technical problems from discovery through production deployment.
  • Ability to explain complex technical concepts to engineers, customers, and executive stakeholders.

Responsibilities

  • Build the statistical and machine learning capabilities that power autonomous AI agents operating on complex enterprise data.
  • Design models for anomaly detection, forecasting, optimization, root-cause analysis, and decision support.
  • Analyze large, multi-source enterprise datasets spanning structured, unstructured, operational, and time-series data.
  • Partner with AI engineers to build agentic workflows that can query data, evaluate evidence, generate insights, and support customer decisions.
  • Translate ambiguous customer challenges into scalable, production-ready AI solutions.
  • Develop reusable analytical capabilities that become core platform features used across multiple customer deployments.
  • Establish best practices for experimentation, model evaluation, governance, and operational reliability.
  • Mentor engineers and data scientists while helping raise the technical bar across the organization.

Desired Qualifications

  • Experience building AI agents, LLM-powered applications, or retrieval-augmented generation and tool-calling workflows.
  • Experience with agent frameworks such as LangGraph, CrewAI, AutoGen, ADK, or similar technologies.
  • Experience with model evaluation, observability, or human feedback systems.
  • Experience with modern cloud and data platforms such as AWS, GCP, Azure, Databricks, Snowflake, Spark, or Kubernetes.
  • Collaborative mindset and passion for mentoring others while continuing to learn and grow.

About the Company

Emergence AI

Orchestrates multi-agent AI for enterprise automation

Emergence AI builds autonomous AI agents and orchestration systems that automate and scale enterprise workflows. Its flagship Emergence Orchestrator acts as a meta-agent that plans, assigns tasks to suitable models or agents, executes them, and verifies results via APIs or by navigating web interfaces. It can create new specialized agents in real time from natural language prompts, enabling recursive intelligence and broad interoperability with clients’ tools, data, and legacy systems. The goal is to enable collaboration among multiple AI agents to tackle complex tasks, improving efficiency and scalability for large organizations across industries like supply chain and semiconductor manufacturing, with a subscription-based API model.

Company size
51-200
Company stage
Late Stage VC
Total funding
$100M
Headquarters
New York City, United States
Founded
2018

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