
1 - 10 employees
Founded 1996
📦 Logistics
🏭 Manufacturing
💼 Consulting
Logistics • Manufacturing • Consulting
Factor Funding Company is a financial services provider specializing in small business funding through various options such as accounts receivable factoring, asset-based loans, and purchase order financing. By converting invoices and receivables into immediate cash, they help businesses quickly improve cash flow without the lengthy processes associated with traditional lending. Their services cater to the needs of small businesses across multiple industries, allowing them to focus on growth and operations while alleviating cash flow concerns.
🔥 0 minutes ago
Where this job comes from
Posted on Factor Funding Company's careers page, not through a job board
First seen by Remote Rocketship 0 minutes ago

1 - 10 employees
Founded 1996
📦 Logistics
🏭 Manufacturing
💼 Consulting
Logistics • Manufacturing • Consulting
Factor Funding Company is a financial services provider specializing in small business funding through various options such as accounts receivable factoring, asset-based loans, and purchase order financing. By converting invoices and receivables into immediate cash, they help businesses quickly improve cash flow without the lengthy processes associated with traditional lending. Their services cater to the needs of small businesses across multiple industries, allowing them to focus on growth and operations while alleviating cash flow concerns.
• Lead technical discovery calls with prospects, surfacing requirements, constraints, and success criteria across data engineering, ML, data science, analytics, and AI engineering use cases. • Design and present ML, AI, and Data Science system architectures live with clients, including RAG, agentic workflows, LLM evaluation pipelines, model serving infrastructure, and end-to-end MLOps. • Translate ambiguous business problems into scoped, deliverable engagements by defining solution approaches, identifying risks, sizing effort, and shaping statements of work alongside Account Executives. • Serve as the deal-side technical authority, defending architectural choices and challenging suboptimal designs. • Build technical proposals, reference architectures, and proof-of-concept plans. • Partner with delivery leadership to hand off won deals, ensuring scope, assumptions, and technical context transfer accurately. • Develop and maintain reusable solution patterns, demos, and reference implementations. • Stay current on the AI/ML landscape and apply that knowledge in client conversations. • Provide feedback to product, delivery, and marketing on prospect needs and offering improvements. • Represent Factored externally through webinars, technical content, conference conversations, and select customer events.
• 5+ years of total professional engineering experience, with a clear track record of increasing technical responsibility and scope. • 3+ years working hands-on as a Senior Engineer in AI Engineering, Machine Learning Engineering, Data Engineering or an adjacent production-focused role. • Demonstrable expertise in machine learning system design: ability to whiteboard end-to-end ML/AI systems live, reason about trade-offs (latency, cost, accuracy, maintainability), and defend choices under technical scrutiny. • Deep practical experience with GenAI/LLM systems: RAG architectures, agentic patterns, evaluation frameworks, prompt and context engineering, fine-tuning approaches, and inference infrastructure. • Working fluency across the broader data stack: data engineering pipelines (batch and streaming), warehouses/lakehouses, feature stores, and analytics workflows — enough to credibly scope work outside pure AI/ML. • Advanced English proficiency, with exceptional written and verbal communication — capable of holding the room with both senior technical stakeholders and executive buyers. • Strong client-facing instincts: comfortable presenting, listening for the real problem under the stated one, and converting ambiguity into a concrete plan. • Track record of execution in fast-paced, ambiguous environments — owns outcomes end-to-end without needing tight supervision. • Structured thinking under time pressure: can decompose a half-formed client problem into a clean architecture in a 60-minute call.
• Ownership through equity participation. • Annual company retreat. • Education bonus for continuous learning. • Company-wide winter break. • Paid time off. • Optional in-person events and meetups. • Tailored career roadmaps. • High-performance culture.
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