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  "job_city": "New York",
  "job_state": "New York",
  "job_title": "AI/ML Engineer / Defence / $500k+ / NYC",
  "job_country": "US",
  "job_benefits": null,
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  "job_posted_at": "8 days ago",
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  "job_highlights": {
    "Benefits": [
      "Up to $500,000+ base salary + equity",
      "Hybrid in NYC",
      "Tight-knit, high-output team",
      "High ownership, real impact, flat structure",
      "$350K+ base + equity - on-site at a VC-backed aerospace startup in NYC"
    ],
    "Qualifications": [
      "Deploying LLM-based systems at scale (Llama, Mistral, GPT-4, Claude)",
      "Retrieval optimisation - hybrid search (BM25 + vector), reranking, caching",
      "Evaluation - recall@k, precision@k, groundedness, hallucination metrics",
      "Fine-tuning (LoRA/QLoRA), RAG architecture, LangChain / LlamaIndex",
      "Tooling: Hugging Face, Weaviate/Pinecone, FastAPI, PyTorch, Redis, Postgres",
      "Monitoring inference, eval automation, & continuous improvement loops",
      "IoT or Hardware integration or real-time systems experience exp",
      "CS or Applied ML degree from a top-tier university",
      "Proven 0-1 experience in a fast-moving AI startup, or Defence related company",
      "You’ve shipped reliable GenAI systems under pressure",
      "Degree in Computer Science from a top-tier university",
      "Prior experience in high-performance teams (0-1, startups)",
      "You’ve shipped real systems - not demos",
      "Technical Deep Dive",
      "Technical Assessment or Live Pairing",
      "Panel focused on mindset & team fit",
      "Deep experience with LLMs, LangChain, Hugging Face & real deployments",
      "Must have shipped working GenAI products, not just prototypes",
      "Ideal: startup DNA, top-tier CS degree, fast execution mindset"
    ],
    "Responsibilities": [
      "You’ll own & scale a RAG-driven AI system powering critical aerospace operations",
      "Expect to tackle retrieval quality, latency bottlenecks, & eval-driven fine-tuning head-on for the most innovative & exciting real-time systems in Aerospace today",
      "Own the LLM pipeline end-to-end – retrieval → evaluation → fine-tuning",
      "Improve accuracy, grounding, and eval metrics continuously",
      "Make architecture decisions for scale, reliability & speed",
      "Collaborate directly with founders & domain experts",
      "Own and improve RAG pipelines - accuracy and latency matter"
    ]
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  "job_description": "Senior AI/ML Engineer - (LLMs / RAG / Agentic Systems) - Aerospace - NYC - $500k+ Equity\n\nWe’re hiring for a world class team at one of the fastest growing & most innovative next-gen aerospace AI companies in North America. They're building LLMs, RAG & high-performance AI systems to power mission-critical operations in defence & space.\n\nOnly the top 0.1% of America's AI Engineers can do this. If you’ve built real mission critical LLM systems that can’t fail - this could be your next move.\n\nThe Role\n\nYou’ll own & scale a RAG-driven AI system powering critical aerospace operations. Expect to tackle retrieval quality, latency bottlenecks, & eval-driven fine-tuning head-on for the most innovative & exciting real-time systems in Aerospace today. This is full production ownership - from architecture to metrics.\n\nYou should have experience with:\n• Deploying LLM-based systems at scale (Llama, Mistral, GPT-4, Claude)\n• Retrieval optimisation - hybrid search (BM25 + vector), reranking, caching\n• Evaluation - recall@k, precision@k, groundedness, hallucination metrics\n• Fine-tuning (LoRA/QLoRA), RAG architecture, LangChain / LlamaIndex\n• Tooling: Hugging Face, Weaviate/Pinecone, FastAPI, PyTorch, Redis, Postgres\n• Monitoring inference, eval automation, & continuous improvement loops\n\nBonus:\n• IoT or Hardware integration or real-time systems experience exp.\n\nIdeal background:\n• CS or Applied ML degree from a top-tier university\n• Proven 0-1 experience in a fast-moving AI startup, or Defence related company\n• You’ve shipped reliable GenAI systems under pressure\n• Degree in Computer Science from a top-tier university\n• Prior experience in high-performance teams (0-1, startups)\n• You’ve shipped real systems - not demos\n\nYou’ll be expected to:\n• Own the LLM pipeline end-to-end – retrieval → evaluation → fine-tuning\n• Improve accuracy, grounding, and eval metrics continuously\n• Make architecture decisions for scale, reliability & speed\n• Collaborate directly with founders & domain experts\n\nStack:\n\nPython / PyTorch / LangChain / Transformers / FastAPI / Hugging Face / Weaviate / Redis / Postgres / Docker / Kubernetes\n\nOffer:\n• Up to $500,000+ base salary + equity\n• Hybrid in NYC\n• Tight-knit, high-output team\n• High ownership, real impact, flat structure\n\nInterview Process:\n\n1) Technical Deep Dive\n\n2) Technical Assessment or Live Pairing\n\n3) Panel focused on mindset & team fit\n\nEqual Opportunity\n\nWe're hiring for an Equal Opportunity Employer.\n\nIf you’ve shipped real GenAI systems, thrive under pressure, and want to see your models power live aerospace systems - this is where theory meets orbit.\n\nTL;DR - Senior AI Engineer (NYC, On-site)\n• Build & scale production-grade GenAI systems from 0 to 1\n• Own and improve RAG pipelines - accuracy and latency matter\n• Deep experience with LLMs, LangChain, Hugging Face & real deployments\n• Must have shipped working GenAI products, not just prototypes\n• Ideal: startup DNA, top-tier CS degree, fast execution mindset\n• $350K+ base + equity - on-site at a VC-backed aerospace startup in NYC\n• All our new jobs are posted here 1st:\n\nlinkedin.com/in/sufyanbashir/",
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  "employer_website": "https://www.opentalent.co",
  "job_onet_job_zone": "5",
  "job_salary_period": "YEAR",
  "job_apply_is_direct": false,
  "job_employment_type": "Full–time",
  "job_employment_types": [
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  "job_posted_at_timestamp": 1773964800,
  "job_posted_at_datetime_utc": "2026-03-20T00:00:00.000Z"
}