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Forward Deployed Engineer

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🔥 18 hours ago

🏄 California – Remote

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⏰ Full Time

🟡 Mid-level

đźź  Senior

👷🏻‍♀️ Engineer

đź‘» Ghost score 12%

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Logo of Fastino Labs

Fastino Labs

11 - 50 employees

đź’Ľ Consulting

🏥 Healthcare

📣 Marketing

đź’° Seed on 2025-08

Consulting • Healthcare • Marketing

Fastino Labs is a company that builds production-ready, task-specific small language models (SLMs) and a fine-tuning platform focused on fast, efficient extraction and classification for agentic AI. Their GLiNER models deliver low-latency, small-footprint inference (often <50 ms and ~200M parameters) that can run on CPU and edge hardware, and can be deployed privately (VPC, on-premises, or on-device). Fastino provides tools to generate synthetic datasets, fine-tune models for domain-specific tasks (e. g. , PII detection, clinical data extraction, ad detection, knowledge-graph extraction), and ship optimized model weights for production use, targeting developer and enterprise workflows.

đź“‹ Description

• Embed with customer engineering teams to scope, build, and deploy Fastino models into their production systems • Write integrations, data pipelines, eval harnesses, and services that run on customer infrastructure, including cloud, VPC, and on-prem environments • Fine-tune and evaluate models on customer data, proving improvements over baselines in accuracy, latency, and cost • Debug authentication, networking, GPU and inference performance, data quality, and edge cases • Own the technical side of deals from first call through go-live, working closely with founders and account executives • Turn field-built solutions into reusable tools, reference architectures, and SDK improvements • Bring customer feedback to research and product teams and advocate for customer needs

🎯 Requirements

• BS or MS in Computer Science or a related field (or equivalent experience) • 3+ years as a software engineer, ideally with some time in a customer facing role (FDE, solutions engineering, consulting, or similar) • Strong in Python • Comfortable with at least one of TypeScript, Go, or Rust • Hands on experience shipping LLM or ML systems to production: APIs, fine-tuning, evals, RAG, or agents • Solid with cloud and infra basics: AWS/GCP/Azure, Docker, Kubernetes, networking, and security • Willing to travel to customer sites as needed • Bonus: experience with GLiNER, NER, or other information extraction models • Bonus: early stage startup experience

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