Senior AI Engineer

Talkspace

WorldwideFully remoteFull TimeSenior, LeadInformation Technology
USD 169,000–200,000 a yearPosted 3mo ago

Why we think you can apply

Hiring model
Open worldwide · the employer states no country restriction
Work from
Anywhere, the UAE included

Posted 3 months ago · apply link checked 4 hours ago

About the role

Responsibilities

  • Design and implement technical architecture for core AI agents, including planning modules and memory systems
  • Apply Reinforcement Learning (RL) and control theory to develop adaptive intervention strategies
  • Select, fine-tune, and deploy Large Language Models (LLMs) for agent reasoning and communication
  • Develop human-agent interaction (HAI) models incorporating cognitive science principles
  • Construct simulation environments for pre-training and testing agent policies
  • Optimize deployment environments for multi-agent orchestration and low-latency decision-making
  • Lead evaluation and adoption of new agentic frameworks and reasoning technologies
  • Design evaluation pipelines including trace-level analysis, production monitoring, and guardrails

Requirements

  • Bachelor’s or Master’s degree in Computer Science, AI, Robotics, or a quantitative field
  • 5+ years of experience in production software engineering
  • 3+ years focused on machine learning or autonomous systems
  • Mastery of Python and scientific libraries
  • Experience with MLOps and CI/CD pipelines for ML models
  • Strong understanding of Reinforcement Learning (RL) and planning algorithms
  • Hands-on experience with LLM fine-tuning, RAG, and prompt engineering
  • Proficiency with AWS, GCP, Docker, and Kubernetes

About the Company

Talkspace is the world’s leading online therapy company, serving over 2 million users through tele-health. Our mission is to make quality mental healthcare simple, accessible, and available to everyone.

What we look for

  • Degree in CS or quantitative field
  • 5+ years software engineering
  • 3+ years ML/autonomous systems
  • Python mastery
  • MLOps expertise
  • LLM deployment experience
  • Cloud infrastructure proficiency
PythonLLMReinforcement Learning
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