Senior AI Scientist

Order.co

AI Scientist/Senior AI Scientist at Order.co transforming business purchasing experiences with applied AI. Leading high-impact initiatives and mentoring junior team members.

Posted 7/24/2026full-timeRemote • New York • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in applied AI and machine learning, with a strong focus on production delivery and the ability to mentor junior scientists. Proficient in designing AI/ML solutions while collaborating effectively across product, engineering, analytics, and operations.

Highest-signal resume keywords

Applied Data ScienceMachine LearningLLM TechnologiesAI-Native Engineering WorkflowsCloud Stack Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Applied Data ScienceMachine LearningModel ProductionizationStatistical ReasoningModel EvaluationAI/ML Solution DesignData DiagnosticsExperimentationKPI DevelopmentTechnical Feasibility Analysis

Soft Skills

CollaborationMentoringDecision-Making

Tools & Technologies

AWSGCPAI/ML FrameworksCodingDebuggingCode Review

Industry Keywords

AI OpportunitiesTechnical StandardsProduction DeliveryHigh-Leverage InitiativesBusiness Context

Tech Stack

Tools & technologies

AWSCloudGoogle Cloud Platform

About the role

Key responsibilities & impact

Ship applied AI from problem definition through deployed production
Own one or more high-leverage initiatives per quarter with clear KPI hypotheses and delivery accountability
Mentor junior scientists and influence technical standards within your initiative scope
Identify high-leverage AI opportunities using business context, data diagnostics, and technical feasibility
Design practical AI/ML solutions with clear trade-offs on accuracy, latency, cost, and reliability
Partner closely with product, engineering, analytics, and operations to align scope, sequencing, and accountability

Requirements

What you’ll need

5–7+ years in applied data science / ML with repeated production delivery
Deep familiarity with current LLM and agent technologies
Demonstrated ability to productionize complex models and model-adjacent systems
Heavy, day-to-day use of AI-native engineering workflows (coding, framing/design, debugging, and code review) for at least the past 18 months.
Working implementation proficiency across at least two technical ecosystems/cloud stacks (for example AWS and GCP)
Strong quantitative foundation in experimentation, statistical reasoning, and model evaluation
Strong collaboration skills; can drive alignment and decisions under ambiguity.

Benefits

Comp & perks

Health insurance
Flexible work hours
Professional development opportunities