Lead Data Scientist - AI-Human Interaction

Jobgether

United States

Hybrid

USD 142,000 - 195,000

Full time

14 days+
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Benefits offered by this job

Competitive base salary
Comprehensive health insurance
Generous paid time off
401(k) retirement plan
Flexible remote work options
Professional development opportunities

Job summary

A tech-centric company in the United States is seeking a Lead Data Scientist to design adaptive AI systems for seamless human interaction. You will mentor a team, develop ML pipelines, and ensure safe AI interactions. The ideal candidate has a Master's degree with over 4 years in research or ML engineering and expertise in AI development. Competitive salary and comprehensive benefits are included.

Qualifications

  • Master's Degree with 4+ years of experience in research/ML engineering.
  • 2+ years leading AI/ML system development.
  • Experience building production-grade AI models.
  • Expertise in supervised learning and reinforcement learning.
  • Strong communication skills.

Responsibilities

  • Develop and manage ML pipelines for human-AI interactions.
  • Design models for intent recognition and personalization.
  • Lead human-in-the-loop data collection.
  • Collaborate with UX and engineering teams.
  • Mentor and guide a team of data scientists.

Skills

Supervised learning
Reinforcement learning from human feedback (RLHF)
Python
SQL
Data analysis/data mining tools
Collaboration skills
Machine learning frameworks (PyTorch, JAX)
Human-computer interaction

Education

Master's Degree in relevant field
Ph.D. in Machine Learning or related field (preferred)

Tools

PyTorch
JAX
LangChain
LangGraph

Job description

Lead Data Scientist - AI-Human Interaction

This range is provided by Jobgether. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Overview

This role leads the design and development of adaptive, human-aware AI systems that interact seamlessly with people across multiple modalities, including text, speech, and interactive interfaces. You will drive the creation of AI models that improve user trust, alignment, and collaboration while ensuring safe and explainable interactions. The position combines cutting-edge research, experimentation, and product-focused execution to enhance user experiences in real-world environments. You will mentor a team of data scientists, collaborate with engineers and product leaders, and define metrics that evaluate the effectiveness of human-AI interactions. The environment is innovative, collaborative, and focused on delivering measurable impact through AI-human collaboration.

Base pay range

$142,000.00/yr - $195,000.00/yr

Responsibilities
  • Develop and manage ML pipelines to evaluate and enhance human-AI interactions across modalities (text, speech, UI/UX, behavioral signals)
  • Design adaptive models for intent recognition, dialog state tracking, preference learning, and multi-turn personalization
  • Lead human-in-the-loop data collection and feedback integration to optimize agent behavior
  • Collaborate with UX, engineering, and safety teams to embed explainability, user control, and alignment into AI systems
  • Develop and monitor human-centered evaluation metrics such as helpfulness, latency, trust calibration, and long-term engagement
  • Conduct causal inference and A/B testing to measure the impact of interaction strategies on user behavior and outcomes
  • Mentor and guide a team of data scientists while working with AI researchers and product leaders to improve interaction frameworks
  • Generate reports, projections, models, and executive-level presentations to support strategic decision-making
Qualifications
  • Master's Degree with 4+ years of experience in research, ML engineering, or applied research focused on production-ready AI solutions
  • 2+ years of experience leading AI/ML system development
  • Proven experience building production-grade AI models with strong UX and behavioral outcomes
  • Expertise in supervised learning, reinforcement learning from human feedback (RLHF), or preference modeling
  • Proficiency in Python, SQL, and data analysis/data mining tools
  • Experience with machine learning frameworks such as PyTorch, JAX, LangChain, or LangGraph
  • Experience with high-performance, large-scale ML systems, language modeling with transformers, and large-scale ETL
  • Strong communication skills and ability to collaborate effectively across data science, product, and engineering teams
  • Preferred: Ph.D. in Machine Learning, Human-Computer Interaction, Cognitive Science, NLP, or related field
  • Preferred: Experience with LLM-based agent/copilot systems, voice assistants, AR/VR interfaces, or embodied agents
  • Familiarity with ethical considerations and safety alignment in interactive AI systems
  • Contributions to human-AI interaction research or open-source tools are a plus
Benefits
  • Competitive base salary: $142,300 - $195,700 USD per year, plus performance-based bonus incentives
  • Comprehensive health, dental, and vision insurance, effective day one
  • Generous paid time off, company holidays, and volunteer leave
  • Paid parental and caregiver leave
  • 401(k) retirement plan with excellent company match
  • Flexible remote work options and home office support
  • Well-being programs and professional development opportunities

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. Our AI evaluates your CV and LinkedIn profile, analyzes your skills, experience, and achievements, and compares your profile to the job\'s core requirements and past success factors to determine your match score. Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role. When necessary, a human review may be performed to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. The final decision and next steps are made by the company\'s internal hiring team.

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