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Job Description
Confido is building an AI-native operating system for brands that sell into brick-and-mortar retail. We’re building intuitive and powerful software paired with AI agents that help brands automate the 1000s of hours of tedious manual work that goes into scaling a brand in retail. Brands like Tropicana and Olipop use our first products in accounting and planning to account for and plan for $Bs of retail revenue.
We have best-in-class growth (5x YoY), efficiency, and we’ve recently raised a $15M Series A to build on the existing momentum.
The Role:
Location: New York, NY (relocation assistance available)
Compensation: $300,000 and $350,000 + Up to 40% Bonus + Benefits + Meaningful Equity (.4% - .7%).
You will be our Founding Staff ML / AI Engineer, setting the foundation for evolving our AI / ML capabilities. We have a unique mix of work across LLMs and advanced machine learning.
Potential Projects:
- Developing agentic systems to retrieve information from legacy systems
- Leverage NLP and LLMs to understand complex documents
- Predict brand sales using advanced machine learning techniques
- Detect anomalies in sales data to help brands sell more
- Recommend the optimal promotion for a brand at a retailer
What You'll Do:
- Own the full AI / ML lifecycle—from research & prototyping to production deployment & monitoring
- Collaborate directly with our CTO and CEO to define our technical and product strategy.
About You:
- Minimum of 5 years of Applied AI / ML experience, ideally in a startup environment
- Strong product mindset—the ability to bridge AI capabilities with real-world usage
- Experience fine-tuning LLMs (Llama, GPT) and designing AI prompt workflows.
- Strong background in ML systems design and engineering best practices
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Job Details
- Category
- Software
- Employment Type
- Full Time
- Location
- New York, NY, US
- Posted
- Apr 7, 2026, 06:40 AM
- Listed
- Mar 24, 2026, 04:29 PM
- Compensation
- $300,000 - $350,000 per year
About Confido
Part of the growing frontier tech ecosystem pushing the edges of what's possible.
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