Principal Applied Scientist – Responsible AI

Claritev•New York, NY

About The Position

The Principal Applied Scientist — Responsible AI is responsible for the design, development, and technical evaluation of AI/ML systems, with a focus on production readiness, model reliability, and technical risk validation. This role serves as the technical authority within the Responsible AI program, ensuring that all AI systems meet defined standards for performance, observability, and risk mitigation prior to production deployment. Your work directly impacts audit readiness, risk mitigation, and the trustworthiness of AI systems used across the business. This role does not own governance frameworks, policy, or enterprise AI architecture, but ensures that AI systems are technically compliant, measurable, and defensible within those frameworks.

Requirements

5 to 8 years of hands‑on experience developing, evaluating, or deploying ML or AI systems in production environments; with strong interest/experience in Responble AI and AI governance.
Expertise in modern ML/AI techniques, including: Large Language Models (LLMs) Generative AI (text, vision, multimodal) Classical ML (supervised, unsupervised, reinforcement learning) Model evaluation and validation methodologies
Deep understanding of AI system risks, including bias, hallucination, robustness, drift, data leakage, and safety failure modes.
Proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX, HuggingFace, Ray, MLflow, or equivalent).
Must have strong organizational capabilities to manage and prioritize multiple complex AI initiatives simultaneously.
Must have strong project management skills to partner through production deployment.
Strong problem-solving, communication, and cross-functional collaboration skills will be key to success in this role that requires collaborating with Core AI Science/Engineering teams, and business stakeholders.

Nice To Haves

Experience in healthcare or regulated environments strongly preferred!
MS with significant applied experience acceptable. Advanced degree in a quantitative field (Computer Science, Machine Learning, Statistics, Applied Mathematics, Engineering, or related discipline) preferred.

Responsibilities

Model Evaluation & Technical Risk Assessment
Production Readiness & Deployment Standards
Observability & Monitoring
Cross-Functional Technical Leadership
Innovation & Applied Research
Mentorship & Technical Standards
Governance Alignment (Non-Ownership)
Technical Planning, Prioritization & Pipeline Management

Benefits

Medical, dental and vision coverage with low deductible & copay
Life insurance
Short and long-term disability
Paid Parental Leave
401(k) + match
Employee Stock Purchase Plan
Generous Paid Time Off – accrued based on years of service
WA Candidates: the accrual rate is 4.61 hours every other week for the first two years of tenure before increasing with additional years of service
10 paid company holidays
Tuition reimbursement
Flexible Spending Account
Employee Assistance Program
Sick time benefits – for eligible employees, one hour of sick time for every 30 hours worked, up to a maximum accrual of 40 hours per calendar year, unless the laws of the state in which the employee is located provide for more generous sick time benefits.