3 days ago

AI/ML Engineer, Conversational AI

Fanatics

Hybrid
Full Time
$200,000
Hybrid

Job Overview

Job TitleAI/ML Engineer, Conversational AI
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$200,000
LocationHybrid

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Job Description

About Fanatics Markets

Fanatics Markets is the real-money prediction and trading app where you can invest in moments you care about. Built on a secure platform, we let users predict real-world outcomes and trade on events they actually follow - from sports and entertainment to political elections and beyond. Our mission is to redefine how fans engage with the moments and markets that matter most. We're looking for the right people to help us build the future of prediction markets.

Fanatics Betting and Gaming is seeking an AI/ML Engineer, Conversational AI on our cross-functional Applied AI team that is on a mission to 10x FBG with AI. You’ll build and productionize the software foundations that power next-gen recommenders, autonomous AI agents, and scalable AI-driven experiences—working in a fast-paced, startup-style environment where you’ll move from prototype to ship-ready features in days, not months. As an AI Engineer at Fanatics, you will partner with Applied Scientists, Data Engineers, and Product teams to design, implement, and maintain end-to-end systems that deliver autonomous agent capabilities to internal stakeholders and millions of fans. You’ll translate cutting-edge research into rock-solid code, architect microservices for low-latency inference, and champion best practices in reliability, scalability, and observability.

Responsibilities

  • Engineer Conversational ML for Support Tools: Design, fine-tune, and productionize dialogue models—integrating RAG pipelines, context-aware routing, and continuous feedback loops—to power internal workflows that supercharge customer-support agents while hitting sub-100 ms latency and enterprise-grade reliability.
  • Develop AI Agent Frameworks: Create, integrate, and extend agent orchestration pipelines—building tools to deploy, monitor, and iterate on multi-agent workflows.
  • Collaborate in a Startup-Like Pod: Work hands-on across the stack: from data ingestion and feature engineering to model deployment and UX integration—rapidly prototyping and shipping proof-of-concepts alongside engineers and product managers.
  • Optimize for Scale & Reliability: Implement CI/CD for model updates, containerize inference workloads (Docker/Kubernetes), and instrument services with logging, tracing, and alerts to meet 99.9% uptime SLAs.
  • Champion Engineering Best Practices: Write clear, maintainable code; conduct code reviews; mentor junior teammates; and evangelize automated testing, code linting, and performance monitoring.

Skills & Qualifications

  • 7 years of professional software engineering experience, with at least 2 years focused on AI/ML systems such as conversational AI, customer support, copilot and/or chatbot experiences.
  • Hands-on experience building and deploying models in production.
  • Hands-on experience with MCP (Model Context Protocols).
  • Proficiency in Python (FastAPI, Flask) and familiarity with strong-typed languages (Java, Go, or C#) for microservice development.
  • Experience with container orchestration (Docker, Kubernetes) and cloud platforms (AWS, GCP, or Azure).
  • Knowledge of AI agents and frameworks (e.g. LangChain, Ray RLlib, custom orchestrators).
  • Solid understanding of distributed systems, API design, and data pipelines.
  • Comfortable navigating ambiguity in a startup-like environment: you’re resourceful, rapid in iteration, and thrive on end-to-end ownership.

Ready to build the future of sports betting? If you possess some of these skills but not all of them, we still encourage you to apply!

Salary Range

$152,000 – $250,000 USD per year

Key skills/competency

  • Conversational AI
  • Machine Learning
  • AI Agents
  • Python
  • Cloud Platforms
  • Docker
  • Kubernetes
  • Microservices
  • RAG Pipelines
  • Dialogue Models

Tags:

AI/ML Engineer
Conversational AI
Machine Learning
Dialogue Models
AI Agents
Microservices
RAG Pipelines
Productionization
Distributed Systems
API Design
Customer Support Tools
Python
FastAPI
Flask
Java
Go
C#
Docker
Kubernetes
AWS
GCP
Azure
LangChain
Ray RLlib

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How to Get Hired at Fanatics

  • Research Fanatics's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
  • Tailor your resume: Highlight your experience in AI/ML, conversational AI, Python, cloud platforms, and distributed systems, aligning with the AI/ML Engineer, Conversational AI role.
  • Showcase project work: Prepare to discuss real-world projects involving dialogue models, AI agents, microservices, and production deployments.
  • Prepare for technical interviews: Brush up on algorithms, data structures, system design, and AI/ML concepts relevant to conversational AI.
  • Demonstrate problem-solving: Be ready to share examples of navigating ambiguity and thriving in fast-paced, iterative development environments.

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