Staff ML Engineer

5 days ago

New York, New York, United States The Lanes Group Full time $150,000 - $250,000 per year

Staff Machine Learning Engineer – Semantic Search & RAG Systems

Location:
New York - Hybrid

Seniority:
Staff / Senior Level (6+ years)

About the Role

We're looking for a Staff Machine Learning Engineer to lead the development of systems powering semantic search and retrieval-augmented generation (RAG) across a fast-scaling AI platform.

You'll take ownership of search relevance, data structuring, and personalization — directly shaping how users discover and engage with the most impactful opportunities in the market.

This is a high-impact role for an engineer who thrives at the intersection of LLMs, data architecture, and intelligent retrieval, and wants to push the boundaries of AI-powered search and recommendation systems.

Key Responsibilities

1. Own Semantic Understanding

  • Define and execute the roadmap to improve search precision and recall.
  • Design optimized data pipelines for embeddings and fine-tuned models.
  • Develop and experiment with advanced retrieval and ranking strategies to continuously improve result quality.
  • Implement novel LLM-driven approaches that elevate semantic relevance and accuracy.

2. Architect RAG & Personalization Systems

  • Build pipelines for contextualized, individualized responses using both implicit and explicit user data.
  • Design scalable architectures that integrate and retrieve information across multiple data types (notes, documents, interactions, historical searches, etc.).
  • Implement RAG systems that personalize and adapt to user behaviour in real time.

3. Cross-Team Collaboration

  • Work with infrastructure and product engineering teams to deploy scalable ML frameworks.
  • Generalize RAG and search architectures for use across the wider platform and product ecosystem.

What We're Looking For

Experience & Background

  • 6+ years as a Machine Learning Engineer, including hands-on experience with LLM-powered search, RAG implementations, or agentic workflows.
  • Proven record of improving semantic search, embeddings, vector stores, and ranking pipelines with measurable impact.
  • Previous success in a Tier-1 venture-backed startup or similarly fast-moving, innovative environment.

Technical Expertise

  • Deep understanding of LLMs, embeddings, and vector database technologies.
  • Strong applied experience with retrieval-augmented generation and personalized recommendation systems.
  • "AI-native" mindset — actively engages with the latest model releases, frameworks, and AI tools.

Soft Skills & Mindset

  • High energy, enthusiasm, and a collaborative mindset.
  • Naturally curious and driven, with clear passion in a chosen field (e.g., blog, open-source work, or community projects).
  • User-first approach, with the ability to balance technical depth and product vision.
  • Excitement for building within a startup and curiosity about mission-driven innovation.

Why Join

You'll be working at the cutting edge of applied AI — improving how people discover insights, opportunities, and innovation itself. Every improvement you make to our search and RAG systems directly impacts real-world outcomes and accelerates discovery at scale.

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