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Ai Scientist Salary In Jobs (NOW HIRING)

Order.co

AI Scientist / Senior AI Scientist

Founded in 2016 and headquartered in New York City, Order.co oversees nearly half a billion in annualized spend across hundreds of customers like WeWork, SoulCycle, Lume, and [solidcore]. Order.co ...

Mistral AI

AI Scientist

New York, NY · On-site

Our diverse workforce thrives in competitive environments and is committed to driving innovation ... The Role As an AI Scientist , you will research and develop novel methods to advance the ...

Gehc

AI Scientist

North East, PA

Summary The AI Scientist will work in teams addressing statistical, machine learning and data ... In this role, you will contribute to the development and deployment of modern machine learning ...

Kiongroup

AI Scientist

Atlanta, GA · On-site

$98K - $123K/yr

We are seeking an AI Scientist to join our Data Platform and AI team within Software Product ... What You Will do in This Role: * Translate business problems in intralogistics planning and ...

Kiongroup

AI Scientist

Atlanta, GA · On-site

$98K - $123K/yr

We are seeking an AI Scientist to join our Data Platform and AI team within Software Product ... What You Will do in This Role: * Translate business problems in intralogistics planning and ...

GE HealthCare

AI Scientist

Bellevue, NE · On-site

Summary The AI Scientist will work in teams addressing statistical, machine learning and data ... In this role, you will contribute to the development and deployment of modern machine learning ...

BillGO, Inc.

AI Scientist

Fort Collins, CO

AI Scientist: Shape the future of payments powered by AI/ML BillGO is building future of B2B ... Build AI/ML solutions embedded directly in B2B payment flows, such as: * Intelligent payment ...

Medpace, Inc.

AI Scientist

Cincinnati, OH

Do you have a background in data science and/or computer science with experience working with AI tools for interactive AI applications across various IT systems? If so, we have an exciting ...

Intuit

Staff AI Scientist

Atlanta, GA · On-site

Intuit is looking for an innovative and hands-on Staff AI Scientist to join the Intuit AI team ... In this role you will be building and deploying machine learning models using both analytical ...

Intuit

Staff AI Scientist

Atlanta, GA

Intuit is looking for an innovative and hands-on Staff AI Scientist to join the Intuit AI team ... In this role you will be building and deploying machine learning models using both analytical ...

Intuit

Staff AI Scientist

Mountain View, CA · On-site

$209K - $283K/yr

Intuit is looking for innovative and hands-on Staff AI Scientist to join the GTM Tech platform AI ... In this role you will be building and deploying machine learning models using both analytical ...

Medpace, Inc.

AI Scientist

Cincinnati, OH · On-site

Do you have a background in data science and/or computer science with experience working with AI tools for interactive AI applications across various IT systems? If so, we have an exciting ...

Intuit

Staff AI Scientist

Manhattan, NY · On-site

$209K - $283K/yr

Intuit is looking for an innovative and hands-on Staff AI Scientist to join the Intuit AI team ... In this role you will be building and deploying machine learning models using both analytical ...

Intuit

Staff AI Scientist

Mountain View, CA

$209K - $283K/yr

Intuit is looking for an innovative and hands-on Staff AI Scientist to join the Intuit AI team ... In this role you will be building and deploying machine learning models using both analytical ...

BillGO, Inc.

AI Scientist

Fort Collins, CO · On-site

$132K - $196K/yr

AI Scientist: Shape the future of payments powered by AI/ML BillGO is building future of B2B ... Build AI/ML solutions embedded directly in B2B payment flows, such as: * Intelligent payment ...

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All JobsAi Scientist Salary In Jobs

Ai Scientist Salary In information

Which 3 jobs will survive AI?

AI scientists and related roles such as data scientists and machine learning engineers are expected to continue thriving due to the need for developing, managing, and improving AI systems. These jobs require specialized skills in programming, statistics, and domain knowledge, making them less susceptible to automation. Continuous learning and staying updated with new AI tools and techniques are essential for long-term job security in this field.

What is the difference between Ai Scientist Salary In vs Data Scientist?

AspectAi ScientistData Scientist
Average Salary$115,000$105,000
Required CredentialsMaster's or PhD in AI, Machine Learning, or related fieldsMaster's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, tech companies, AI startupsBusiness analytics, consulting firms, tech companies
Industry UsageDeveloping AI models, machine learning algorithmsAnalyzing data, building predictive models

While Ai Scientists focus on developing artificial intelligence and machine learning models, Data Scientists analyze data to extract insights. Salaries for Ai Scientists tend to be higher due to specialized skills in AI development, but both roles require advanced degrees and are in high demand across tech industries.

What is a $900000 AI job?

A $900,000 AI job typically refers to senior or executive roles such as AI research directors, chief AI officers, or lead data scientists, often found in large tech companies or specialized firms. These positions require advanced skills in machine learning, deep learning, and extensive experience, and may include bonuses, stock options, or other compensation components that contribute to the high total salary.

What are the key skills and qualifications needed to thrive as an AI Scientist, and why are they important?

To thrive as an AI Scientist, you need advanced expertise in machine learning, deep learning, mathematics, and programming, typically supported by a master's or Ph.D. in computer science or a related field. Familiarity with technical tools such as Python, TensorFlow, PyTorch, and cloud platforms, as well as relevant certifications, is highly valued. Strong problem-solving, critical thinking, and collaboration skills help AI Scientists stand out in multidisciplinary environments. These skills are crucial for innovating effective AI solutions and driving successful project outcomes in a rapidly evolving field.

What factors influence salary ranges for AI Scientists in India?

AI Scientist salaries in India can vary widely depending on factors such as years of experience, level of education, industry sector, and the size or reputation of the employing organization. Those with advanced degrees or expertise in specialized machine learning domains typically command higher salaries. Additionally, working for multinational tech firms or research-driven startups in major cities often comes with competitive compensation packages and additional perks. It's also important to note that demonstrated experience in deploying AI solutions and collaborating on interdisciplinary teams can positively impact salary offers.

How much money do AI scientists make?

AI scientists typically earn a median salary ranging from $100,000 to $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in machine learning, deep learning, and programming languages like Python or TensorFlow can command higher salaries, often exceeding $200,000 per year.

What engineer makes $500,000 a year?

Senior AI scientists and machine learning engineers with extensive experience, advanced skills in deep learning, and strong industry reputations can earn salaries around $500,000 annually, especially in high-demand sectors like technology and finance. Such roles often require advanced degrees, specialized knowledge, and leadership responsibilities.

What is the average salary of an AI Scientist?

The average salary of an AI Scientist can vary based on factors like experience, education, location, and the specific industry. In the United States, AI Scientists typically earn between $110,000 and $180,000 per year, with more experienced professionals or those in high-demand locations potentially earning even higher salaries. Large tech companies and research institutions often offer competitive compensation packages that may include bonuses, equity, and additional benefits. Entry-level positions may start at a lower range, while senior or specialized roles can command salaries well above the average.
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Ai Scientist Salary In jobs near you
Infographic showing various Ai Scientist Salary In job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution.
AI Scientist / Senior AI Scientist

AI Scientist / Senior AI Scientist

Order.co

Remote

Full-time

Posted 4 days ago

Job description

Order.co is the System of Action for the Office of the CFO, transforming the way businesses purchase and pay into an intuitive, B2C-like shopping experience. Order.co leverages embedded AI agents and embedded financial products to reinvent the way businesses connect with their vendors.
End users enjoy a seamless, zero-training buying experience, while finance and procurement leaders gain a single platform to orchestrate how the business "should operate". The result is an all-in-one solution that serves as a gravitational pull for spend and data, automating and eliminating procurement and finance workflows from requisition to reconciliation along the way.
Order.co is on the cutting edge of B2B Agentic Commerce, poised to be the market leader in creating a more predictive, prescriptive, and personalized experience for users.
Founded in 2016 and headquartered in New York City, Order.co oversees nearly half a billion in annualized spend across hundreds of customers like WeWork, SoulCycle, Lume, and [solidcore]. Order.co has raised $75M in funding from industry-leading investors like MIT, Stage 2 Capital, Rally Ventures, 645 Ventures, and more. Order.co has been proudly named a 50 to Watch by Spend Matters and a Best Place to Work by BuiltIn and Inc. Magazine.
Role summary
We are hiring an AI Scientist or Senior AI Scientist to ship applied AI from problem definition through deployed production, with direct accountability for measurable business outcomes.
This is an embedded role on a product engineering squad building customer-facing ordering and workflow capabilities. Final title and scope are set based on the experience and impact demonstrated in our interview process.
Success at either level means iterative, low-cycle-time delivery that compounds into meaningful KPI movement. Scope grows through the magnitude and reach of impact, not through long delivery windows.
How expectations differ by level
Dimension
AI Scientist
Senior AI Scientist
Scope
Owns one or more high-impact initiatives end-to-end (problem definition → production → KPI impact)
Owns a portfolio of AI opportunities across teams; sets prioritization, not only execution
Level of Impact
Measurable KPI movement on assigned initiatives
Company-priority KPI movement with cross-team reach
Technical leadership
Leads initiative design, rollout, failure-mode handling, and model-operations playbooks for owned systems
Leads architecture and delivery patterns others adopt; raises team-wide model-to-production standards
Mentorship
Mentors junior colleagues; improves standards within initiative scope
Mentors experienced ICs; shapes cross-team technical direction
Stakeholder reach
Strong influence within embedded squad and data partners
Aligns senior stakeholders across product, engineering, and operations on AI bets
Experience signal
5-7+ years in applied data science / ML with repeated production delivery
8+ years with portfolio-level outcome ownership
How to read this: If your strongest proof is initiative-level execution with production impact and hands-on delivery, AI Scientist may fit. If you have repeatedly owned portfolio-level AI bets across teams-with prioritization authority and standards others follow-Senior AI Scientist may fit.
About the work
Near-term focus areas include:
  • Predictive ordering - ML and AI capabilities that improve how customers plan and place orders
  • Agentic copilots for workflow management - intelligent assistance embedded in core product workflows (technical direction weighted toward Senior AI Scientist hires)

You will be embedded day-to-day with a product/engineering squad while reporting into the data team.
Scope and ownership
Shared Expectations
  • Lead end-to-end lifecycle execution: problem framing, experimentation, model/system design, production rollout, and post-launch optimization that incorporate HITL feedback.
  • Be accountable for business outcomes (for example conversion, margin, operational efficiency, retention)-not model metrics alone.
  • Translate ambiguous business goals into clear technical bets, delivery plans, and measurable success criteria.
  • Ship iteratively with short feedback loops; deliver meaningful impact at each step.

AI Scientist
  • Own one or more high-leverage initiatives per quarter with clear KPI hypotheses and delivery accountability.
  • Balance model quality, operational constraints, and time-to-value on assigned bets.
  • Define rollout strategy, failure modes, and iterative improvement loops for systems you own.
  • Establish model-operations playbooks for incident response and performance degradation on owned systems.
  • Mentor junior scientists and influence technical standards within your initiative scope.

Senior AI Scientist
  • Own a portfolio of AI opportunities tied to company-priority KPIs across multiple teams.
  • Identify and prioritize highest-leverage opportunities; build the execution path, not only execute assigned work.
  • Lead architecture and operational patterns for scalable model delivery that others can reuse.
  • Raise team standards through repeatable model-to-production patterns, implementation quality, and decision velocity.
  • Mentor experienced ICs and align senior stakeholders on AI prioritization and sequencing.

Core responsibilities
Shared Responsibilities
  • Identify high-leverage AI opportunities using business context, data diagnostics, and technical feasibility.
  • Design practical AI/ML solutions (leveraging both deterministic and LLM/agent-based patterns where appropriate) with clear trade-offs on accuracy, latency, cost, and reliability.
  • Build and productionize complex model systems with engineering-quality discipline: testing, observability, rollback/fallback strategy, human-in-the-loop integration, and incident readiness.
  • Define evaluation frameworks that connect offline/online model quality to KPI impact and risk/accuracy controls.
  • Partner closely with product, engineering, analytics, and operations to align scope, sequencing, and accountability.

AI Scientist
  • Drive hands-on delivery on predictive ordering capabilities from early production through optimization.
  • Work closely with a principal-level data scientist on architecture choices while owning execution velocity.

Senior AI Scientist
  • Set technical direction for agentic workflow / copilot capabilities in partnership with product and engineering leadership.
  • Co-own prioritization and standards with product, engineering, and data leadership - not execution alone.
  • Mentor scientists and technical peers on applied AI execution, production quality, and pragmatic delivery.

Required qualifications
Baseline
  • Proven track record delivering AI/ML systems to production with measurable business outcomes.
  • Deep familiarity with current LLM and agent technologies, including practical evaluation and failure-mode handling.
  • Demonstrated ability to productionize complex models and model-adjacent systems with strong reliability and observability practices.
  • 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.

AI Scientist Level
  • 5-7+ years in applied data science / machine learning roles with repeated production delivery.
  • Track record owning initiatives end-to-end-not only contributing to models owned by others.
  • Leadership-level influence within a cross-functional squad; improves team decision quality through technical rigor.

Senior AI Scientist Level
  • 8+ years in applied data science / machine learning roles with portfolio-level outcome ownership.
  • Track record owning AI/ML initiatives from concept through production and measurable business impact at cross-team scope.
  • Stakeholder leadership across product, data, engineering, and operations; can resolve prioritization under ambiguity.

Preferred qualifications
  • Experience implementing local/self-hosted AI solutions (for example self-managed agent infrastructure on-prem or in your own environment).
  • Experience with retrieval systems, vector search, ranking/recommendation, or other production AI personalization workflows.
  • Experience in e-commerce, B2B vendor management, financial products, or external systems integrations.

Senior AI Scientist (additional)
  • Experience setting team-level standards for model governance, monitoring, and responsible AI practices.
  • Experience mentoring senior ICs and shaping cross-team technical direction.

What success looks like (first 6 - 9 months)
AI Scientist
  • Launches two or more AI capabilities to production on predictive ordering with clear KPI hypotheses and measurable outcome movement.
  • Establishes reliable model-operations practices (testing, observability, incident playbooks) for owned systems.
  • Delivers iteratively with low cycle time; each release produces an evaluable business signal.
  • Builds effective working rhythm with principal-level data scientist partner and embedded product squad.

Senior AI Scientist
  • Everything above, plus:
  • Launches AI capabilities across more than one initiatives with measurable KPI impact at company-priority scope.
  • Establishes a repeatable, low-cycle-time model delivery pattern adopted by others on the team.
  • Creates durable alignment across product, engineering, and data stakeholders on AI prioritization and execution.
  • Defines technical trajectory for agentic workflow / copilot capabilities alongside predictive ordering.

Working model
  • Embedded squad: Day-to-day work alongside product/engineering on customer-facing capabilities.
  • Principal-level pairing: Close collaboration with a principal-level scientist on architecture, prioritization, and execution-hands-on-keyboard from day one.
  • Cross-functional partners: Product, engineering, analytics, and operations.
  • Leveling at offer: Title reflects scope and impact demonstrated in process, not tenure alone.

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