Machine Learning Engineer

Job not on LinkedIn

🕒 July 27

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 20%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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interVal

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2019

☁️ SaaS

💳 Fintech

🤖 Artificial Intelligence

💰 $1.2M Seed Round - InterVal on 2021-04

SaaS • Fintech • Artificial Intelligence

interVal is a SaaS platform that uses machine learning and natural language processing to extract, analyze, and surface actionable insights from year-end financial and tax documents. It transforms raw financial statements and integrated bookkeeping data (QuickBooks Online, Xero, Sage, Caseware) into valuation metrics, business health KPIs, protection gaps, loan and investment signals, and client-ready reports to help wealth managers, accounting firms, banks, and other financial institutions identify opportunities and grow AUM. The platform emphasizes enterprise-grade security (SOC 2 Type II, AWS hosting), automated advisory workflows, and features aimed at making advisors more proactive and efficient when serving SMB clients.

📋 Description

• Develop and deploy models that work with distributed, privacy-preserving enterprise data (structured, unstructured, and time series) • Work closely with our AI team on Val, our internal contextual intelligence framework, including NLP, embedding systems, and semantic search • Collaborate across product and engineering to build robust ML pipelines for data classification, anomaly detection, semantic inference, and explainability • Research and prototype novel applications of machine learning in private and federated contexts, with a focus on enterprise data security • Integrate ML systems into a secure infrastructure governed by on-chain access control and data provenance • Contribute to internal tools and libraries that help automate model training, evaluation, versioning, and monitoring

🎯 Requirements

• 3–6 years of experience in machine learning, data science, or applied AI roles • Strong programming skills in Python, with experience in ML frameworks like PyTorch,TensorFlow, Hugging Face, or similar • Demonstrated experience working with real-world datasets—especially enterprise or high-integrity data (e.g., financial, medical, telemetry, etc.) • Comfort with data privacy techniques such as differential privacy, federated learning, or homomorphic encryption (or strong interest in learning them) • Interest or experience in working with LLMs, embeddings, or knowledge graph-based approaches • Familiarity with the basics of smart contracts or blockchain (Solidity, EVM, etc.) is a plus—but not required.

🏖️ Benefits

• Shape the frontier of AI, blockchain, and enterprise data infrastructure. • Build tools with real-world impact—help global enterprises activate and monetize their most valuable data assets. • Thrive in a sharp, mission-driven team backed by top-tier technical leadership and investors. • Enjoy meaningful equity, flexible work, and the autonomy to innovate where data, AI, and privacy meet.