Axion Ray helps manufacturers detect, investigate, and resolve product quality issues earlier by applying AI to operational and customer-facing data. The platform ingests structured and unstructured manufacturing and field data, continuously analyzes signals with machine learning models, correlates root causes, and surfaces prioritized quality alerts for cross-functional teams. It provides a shared workspace for quality, service, and engineering teams to manage investigations and track corrective actions. Axion Ray is offered as a B2B SaaS analytics platform for enterprise manufacturers focused on reducing quality costs and improving product performance.
AICustomer SatisfactionDowntime ReductionManufacturingObservabilityPredictiveQualityRoot Cause Analysisaxionray.com
Axion Ray
Axion Ray helps manufacturers detect, investigate, and resolve product quality issues earlier by applying AI to operational and customer-facing data. The platform ingests structured and unstructured manufacturing and field data, continuously analyzes signals with machine learning models, correlates root causes, and surfaces prioritized quality alerts for cross-functional teams. It provides a shared workspace for quality, service, and engineering teams to manage investigations and track corrective actions. Axion Ray is offered as a B2B SaaS analytics platform for enterprise manufacturers focused on reducing quality costs and improving product performance.
AICustomer SatisfactionDowntime ReductionManufacturingObservabilityPredictiveQualityRoot Cause Analysisaxionray.com
HQNew York City, US
Team Size421
Open Jobs9
Total Funding$62M
Latest Fundraise3 months ago
TL;DR
What they do: AI observability platform that detects and prioritizes manufacturing field quality and reliability issues
Customers / focus: Large manufacturers — quality, service, and engineering teams
Founded: 2021
HQ: Brooklyn, New York
Known funding: Seed $7.5M (2023); Series A $17.5M (Mar 2024) — disclosed total ≈ $25M
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Company Overview
Problem Domain
Manufacturing field quality, reliability, and root-cause analysis across distributed service and field data sources.
Series A led by Bessemer Venture Partners with participation from RTX Ventures, Amplo, and Inspired Capital
Investor Signal
“Bessemer Venture Partners led Series A; participation from strategic and sector investors (RTX Ventures, Amplo, Inspired Capital)”
Founders
What we do
Join the Team
Data Operations Lead
On-SiteNew York, US
On-Site • New York, US
Who you are
The ideal candidate blends the structured problem-solving and analytical rigor of top-tier consulting with the executional drive and adaptability of a startup operator
6+ years of experience across data operations, business operations, or strategy, ideally within high-growth tech or AI-driven environments
Background in top-tier management consulting (McKinsey, Bain, or BCG) and/or startup operations with a track record of scaling complex systems
Experience managing large distributed or offshore teams (50+ people, ideally India-based)
Strong analytical and quantitative mindset, comfortable with dashboards, KPIs, and process optimization
Deep understanding of data workflows (collection, labeling, QA) and tooling (e.g., Labelbox, Scale, AWS, or custom pipelines)
Proven ability to operate autonomously, influence cross-functional stakeholders, and drive clarity amid ambiguity
Excellent written and verbal communication skills; able to engage confidently with executives and technical leaders
You’re a builder and operator who thrives in fast-moving, high-accountability environments. You take pride in getting things done — thoughtfully, efficiently, and without drama. You’re energized by ambiguity, skilled at bringing clarity, and comfortable flexing between strategy and execution
You value feedback — giving it, receiving it, and acting on it — and you see collaboration as a competitive advantage, not a burden
You’re low-ego but high-agency: you care about winning as a team more than being right individually. You move quickly, communicate directly, and make decisions grounded in impact and data
You don’t need constant direction — you create momentum. You take ownership for outcomes, and you expect the same from those around you
What the job involves
Teeming tracks opportunities at over 24,000 AI startups, then works with you to find (and land) the one you'll love.
Machine Learning Engineer
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Internship • Austin, US
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Internship • Austin, US
Frontend Developer
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Part-time • Rotterdam, NL
Product Designer
InternshipCambridge, GB
Internship • Cambridge, GB
Technical Writer
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Contract • Austin, US
Technical Writer
Full-timeUtrecht, NL
Full-time • Utrecht, NL
We are seeking a Data Operations Lead to own the performance, structure, and scalability of Axion’s global data operations
This is a highly cross-functional, strategic role at the intersection of data excellence and operational leadership
You’ll be responsible for setting the vision and operational rhythm for Axion’s data organization, ensuring quality, efficiency, and alignment with the broader business
Lead Global Data Operations: Oversee and scale a data operations team based in India, ensuring quality, throughput, and accountability across projects
Build Systems & Processes: Design and implement data workflows, reporting frameworks, and SLAs that enable consistent, high-quality delivery at scale
Bridge Data & Business: Translate business objectives into operational KPIs and data requirements; partner closely with Product, Engineering, and Solutions teams to align on priorities
Operational Analytics: Build visibility into productivity, error rates, and efficiency — using dashboards, root-cause analyses, and continuous improvement frameworks
Leadership Development: Mentor and grow team leads in India to build a high-performance management layer; foster a culture of ownership, clarity, and speed
Cross-Border Execution: Act as the connective tissue between U.S. leadership and India-based operations — ensuring communication, governance, and alignment
Strategic Projects: Lead special initiatives related to data quality, automation, and vendor optimization to drive operational leverage and margin improvement