Machine Learning and AI Engineer - New York

<p data-start="450" data-end="809">You have built real AI systems that ship, break, and get fixed under pressure.<br data-start="528" data-end="531">You care less about model demos and more about decisions that move capital.<br data-start="606" data-end="609">You want your work used daily by professional investors, not buried in notebooks.<br data-start="690" data-end="693">You are comfortable owning hard problems end to end.<br data-start="745" data-end="748">If you want a calm job optimizing benchmarks, this is not it.</p> <h2 data-start="811" data-end="840">The Role, In Plain English</h2> <p data-start="841" data-end="1205">You will build and evolve the AI systems that power Reflexivity’s investment insights.<br data-start="927" data-end="930">This role exists because off-the-shelf models and generic pipelines are not enough.<br data-start="1013" data-end="1016">You will work at the intersection of reasoning engines, proprietary data, and real market impact.<br data-start="1113" data-end="1116">Your work directly affects how investors understand earnings, risk, and market catalysts.</p> <h2 data-start="1207" data-end="1240">What You’ll Be Responsible For</h2> <ul> <li data-start="1243" data-end="1345">Design, fine-tune, and deploy ML and LLM-driven systems used in production by professional investors</li> <li data-start="1348" data-end="1428">Build and maintain inference pipelines that are fast, observable, and reliable</li> <li data-start="1431" data-end="1516">Integrate OpenAI, Gemini, and Anthropic models into reasoning and knowledge systems</li> <li data-start="1519" data-end="1605">Work closely with backend engineers to productionize models in Golang-based services</li> <li data-start="1608" data-end="1657">Improve signal quality, not just model accuracy</li> <li data-start="1660" data-end="1728">Review code and designs with a bias toward long-term maintainability</li> </ul> <h2 data-start="1730" data-end="1768">What “Good” Looks Like in This Role</h2> <p data-start="1769" data-end="1895"><strong data-start="1769" data-end="1788">After 3 months:</strong><br data-start="1788" data-end="1791">You understand the product, data flows, and investor use cases deeply. You ship meaningful improvements.</p> <p data-start="1897" data-end="2014"><strong data-start="1897" data-end="1916">After 6 months:</strong><br data-start="1916" data-end="1919">You own major parts of the AI stack. Your work improves insight quality and latency measurably.</p> <p data-start="2016" data-end="2146"><strong data-start="2016" data-end="2036">After 12 months:</strong><br data-start="2036" data-end="2039">You are a technical reference point for AI decisions. You raise the bar for how AI is built at Reflexivity.</p> <h2 data-start="2148" data-end="2175">Who You Are (Must-Haves)</h2> <ul> <li data-start="2178" data-end="2240">5 plus years building ML or applied AI systems in production</li> <li data-start="2243" data-end="2309">Startup experience working on a core product, not a side project</li> <li data-start="2312" data-end="2382">Strong Python skills and experience integrating with backend systems</li> <li data-start="2385" data-end="2463">Hands-on experience with AI-assisted coding tools like Cursor or Claude Code</li> <li data-start="2466" data-end="2527">Fintech experience or strong personal investment background</li> <li data-start="2530" data-end="2573">Comfortable owning outcomes, not just tasks</li> </ul> <h2 data-start="2575" data-end="2611">Nice-to-Haves (Not Deal Breakers)</h2> <ul> <li data-start="2614" data-end="2673">Experience with LLM reasoning systems or knowledge graphs</li> <li data-start="2676" data-end="2718">Exposure to Golang-based ML integrations</li> <li data-start="2721" data-end="2773">Prior experience supporting investor-facing products</li> </ul> <h2 data-start="2775" data-end="2789">How We Work</h2> <ul> <li data-start="2792" data-end="2843">In-office team with high trust and high ownership</li> <li data-start="2846" data-end="2917">Direct communication, minimal process, strong opinions backed by data</li> <li data-start="2920" data-end="2989">Engineers are expected to think about product impact, not just code</li> <li data-start="2992" data-end="3064">We move fast when it matters and slow down when correctness matters more</li> </ul> <h2 data-start="3066" data-end="3101">Why This Role Is Worth Your Time</h2> <ul> <li data-start="3104" data-end="3167">Direct influence on how professional investors make decisions</li> <li data-start="3170" data-end="3222">Hard problems at the edge of AI, data, and finance</li> <li data-start="3225" data-end="3264">Real ownership and technical autonomy</li> <li data-start="3267" data-end="3315">Senior peers who care about quality and outcomes</li> </ul> <h2 data-start="3317" data-end="3349">Compensation &amp; Practicalities</h2> <ul> <li data-start="3352" data-end="3411">Base salary: $180,000 to $300,000 depending on experience</li> <li data-start="3414" data-end="3431">Equity included</li> <li data-start="3434" data-end="3468">In-office role based in New York</li> <li data-start="3471" data-end="3491">No agency candidates</li> </ul><div class="content-pay-transparency"><div class="pay-input"><div class="title">Salary Range</div><div class="pay-range"><span>$180,000</span><span class="divider">&mdash;</span><span>$300,000 USD</span></div></div></div>