Machine Learning Engineer
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Job Description
Machine Learning Engineer at Interval solving technical problems related to AI, privacy, and distributed systems. Collaborating to build models using enterprise data while maintaining privacy.
Responsibilities:
- 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.
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