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    "requisitionDescription": "<div><hr id=\"isPasted\"><p><strong>LLM Researcher</strong></p><p><strong>Division:</strong> DATUM, Impac Exploration Services<br><strong>Location:</strong> Remote, Oklahoma City (OK), Houston (TX)<br><strong>Type:</strong> Full-Time</p><p><strong>About the Role</strong></p><p>We&#39;re not hiring you to fine-tune prompts. We&#39;re hiring you to obsolete them.</p><p>DATUM is building a small team of ML researchers who think bigger than today&#39;s architectures. We&#39;re the ML division of a 40-year-old energy company with startup DNA and the resources to match our ambitions. While others debate scaling laws, we&#39;re questioning the fundamentals.</p><p>Here&#39;s the deal: We have compute. We have some of the world&#39;s most complex operational data. We have domain experts who&#39;ve been modeling physical systems since before transformers were invented. What we need is someone who sees opportunity where others see constraints.</p><p>This role is for researchers who read papers and think &quot;that&#39;s clever, but here&#39;s what they missed.&quot; Who understand why current architectures fail on certain problems&mdash;and have ideas about what comes next. Who can ship code on Monday and submit to NeurIPS on Friday.</p><p>Fair warning: Do exceptional work here and you&#39;ll probably get poached. When OpenAI or Anthropic comes calling with their offer, we&#39;ll write your recommendation letter. Building things that make Big Tech nervous is how we measure success.</p><p><strong>What You&#39;ll Actually Do</strong></p><ul><li>Design and train models that don&#39;t exist yet&mdash;because current approaches aren&#39;t good enough</li><li>Turn energy domain challenges into ML breakthroughs (think: models that understand physics, not just language)</li><li>Prototype fast, fail faster, and ship the stuff that works</li><li>Write papers that matter. Open source what you can. Give talks that get noticed.</li><li>Work directly with operators and engineers who will actually use what you build</li><li>Have genuine freedom to pursue &quot;what if we tried...&quot; ideas with real compute behind them</li></ul><p><strong>Requirements</strong></p><ul><li>You&#39;ve trained models from scratch, not just fine-tuned APIs</li><li>Deep understanding of transformers and what comes after them</li><li>Track record of original thinking in ML (papers, code, or products)</li><li>Python/PyTorch/JAX fluency&mdash;you build, not just theorize</li><li>Comfort with ambiguity and ability to find signal in noisy, real-world data</li><li>You explain complex ideas simply and challenge assumptions respectfully</li><li><strong>We are not currently sponsoring visas or participating in CPT programs at this time</strong></li></ul><p><strong>Bonus Points</strong></p><ul><li>Published ML research or significant open-source contributions</li><li>Experience with scientific computing, physics-informed ML, or industrial systems</li><li>You&#39;ve built something that surprised even you</li><li>Comfortable in environments where the roadmap is &quot;let&#39;s find out&quot;</li></ul><p><strong>Why This Matters</strong></p><p>Energy is a trillion-dollar industry running on Excel and intuition. The intersection of ML and energy systems is barely explored. While everyone else fights over consumer chatbots, we&#39;re working on problems that actually move the needle on energy independence, efficiency, and human progress.</p><p>If you want to optimize ad clicks, this isn&#39;t for you. If you want to build models that understand how the physical world works&mdash;and ship them to people who operate it&mdash;let&#39;s talk.</p></div>\n",
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