Qureos Mentor

Proximity Works

<div><p>Join Proximity Works, one of the world&rsquo;s most ambitious AI technology companies, shaping the future of Sports, Media, and Entertainment. Since 2019, Proximity Works has created and scaled AI-driven products used by 697 million daily users, generating $73.5 billion in enterprise value for our partners. With headquarters in San Francisco and offices in Los Angeles, Dubai, Mumbai, and Bangalore, we partner with some of the biggest global brands to solve complex problems with cutting-edge AI.</p><p>
We are looking for a Senior Data Scientist with deep expertise in large language models (LLMs), retrieval-augmented generation (RAG), and multimodal learning to shape the next generation of intelligent, scalable, and reliable search systems.<br>
<br>
Role Summary</p><p>
This is a hands-on applied science role at the frontier of AI. You will design, fine-tune, and optimize large-scale language and multimodal models, with a strong focus on retrieval and search. You will productionize retrieval-augmented pipelines, develop ranking and relevance techniques, and define robust evaluation frameworks. You will work closely with engineering and product teams to build systems that combine language, vision, and retrieval modalities &mdash; powering high-quality, real-world search and discovery experiences at scale.</p><p></p><h3 class="jobSectionHeader"><b>
What You&rsquo;ll Do</b></h3><ul>
<li>Design, fine-tune, and optimize LLMs for applied multimodal generation use cases.</li>
<li>Build and productionize RAG pipelines that combine embedding-based search, metadata filtering, and LLM-driven re-ranking/summarization.</li>
<li>Apply prompt engineering, RAG techniques, and model distillation to improve grounding, reduce hallucinations, and ensure output reliability.</li>
<li>Define and implement evaluation metrics across semantic search (nDCG, Recall@K, MRR) and generation quality (grounding accuracy, hallucination rate).</li>
<li>Optimize inference pipelines for latency-sensitive use cases with strategies like token budgeting, prompt compression, and sub-100ms response targets.</li>
<li>Train and adapt models via transfer learning, LoRA/QLoRA, and checkpoint reloading, ensuring robust deployment in production environments.</li>
Collaborate with product and research teams to explore innovative multimodal integrations for user-facing applications.<br>
<li>
</li></ul><p></p><h3 class="jobSectionHeader"><b>What Success Looks Like</b></h3><ul>
<li>Deployment of production-ready LLM + RAG pipelines powering global-scale search and discovery applications.</li>
<li>Demonstrable improvements in grounding accuracy and hallucination reduction across deployed systems.</li>
<li>Consistent delivery of sub-100ms inference latency for generation workloads.</li>
<li>Adoption of rigorous evaluation metrics that drive continuous model improvement.</li>
<li>Effective cross-functional collaboration with engineering, product, and research teams.</li>
</ul><p><b>Requirements</b></p><h3 class="jobSectionHeader"><b>
What You&rsquo;ll Need</b></h3><ul>
<li>Strong background in NLP, machine learning, and multimodal AI.</li>
<li>Proven hands-on experience in LLM fine-tuning, RAG, distillation, and evaluation of foundation models.</li>
<li>Expertise in semantic search and retrieval pipelines (e.g., FAISS, Weaviate, Vespa, Pinecone).</li>
<li>Demonstrated ability to deploy models at scale, including distributed inference setups.</li>
<li>Solid understanding of evaluation frameworks for ranking, retrieval, and generation.</li>
<li>Proficiency in Python, PyTorch/TensorFlow, and modern ML toolkits.</li>
<li>Experience in multimodal AI (bridging text, vision, or speech with LLMs).</li>
<li>Track record of shipping latency-sensitive AI products.</li>
<li>Strong communication skills and the ability to collaborate with cross-functional global teams.</li>
</ul><p></p><h3 class="jobSectionHeader"><b>Success Traits</b></h3><p>
Builder&rsquo;s mindset &middot; High ownership &middot; Analytical clarity &middot; Collaborative spirit &middot; Global mindset &middot; Growth orientation</p><p><b>
Benefits</b></p><h3 class="jobSectionHeader"><b>
Why Join Proximity Works</b></h3><ul>
<li>Work directly on frontier AI problems with some of the world&rsquo;s largest sports, media, and entertainment brands.</li>
<li>Be part of a global-first, high-performance engineering culture.</li>
<li>Competitive compensation aligned with global markets, with remote-first flexibility.</li>
<li>Annual global off-sites with Proxonauts from San Francisco, Dubai, India, and beyond.</li>
<li>High autonomy, direct accountability, and the opportunity to ship AI systems at scale.</li></ul></div>

Senior Data Scientist - LLMs, RAG & Multimodal AI (Remote | Immediate joiner)

<div><p>Join Proximity Works, one of the world&rsquo;s most ambitious AI technology companies, shaping the future of Sports, Media, and Entertainment. Since 2019, Proximity Works has created and scaled AI-driven products used by 697 million daily users, generating $73.5 billion in enterprise value for our partners. Headquartered in San Francisco with offices in Los Angeles, Dubai, Mumbai, and Bangalore, we help global brands discover high-impact AI use cases, build transformative tech stacks, and scale to hundreds of millions of users.</p><p>
If you&rsquo;re excited about building high-performance backend systems at the frontier of AI, this role will give you the opportunity to make global impact.<br>
<br>
Role Summary</p><p>
We are seeking a Backend Engineer to design, build, and scale resilient microservices and APIs that power next-generation AI products. You will partner closely with ML engineers and data scientists to productionize LLMs, RAG pipelines, and multimodal models, ensuring inference is fast, cost-efficient, and production-grade. This is a hands-on role for someone passionate about distributed systems, performance optimization, and bringing cutting-edge AI to millions of users.</p><p></p><h3 class="jobSectionHeader"><b>
What You&rsquo;ll Do</b></h3><ul>
<li>Design and build scalable microservices that power Proximity&rsquo;s AI-driven search and discovery stack.</li>
<li>Develop backend services and APIs to support LLM-powered applications.<br>
Collaborate with ML engineers and data scientists to integrate RAG pipelines, multimodal models, and inference workloads into production.</li>
<li>Optimize inference pipelines for latency, throughput, and cost efficiency (e.g., batching, caching, token budgeting).</li>
<li>Own end-to-end delivery of complex backend projects, from design to deployment and monitoring.</li>
<li>Write high-quality, maintainable code with rigorous testing and fault-tolerant practices.</li>
<li>Drive operational excellence through performance tuning, incident response, and root cause analysis.</li>
Work cross-functionally with Product Managers, Data Scientists, and global engineering teams to translate business needs into scalable technical solutions.<br>
<li>
</li></ul><h3 class="jobSectionHeader"><b>What Success Looks Like</b></h3><ul>
<li>Robust, resilient backend systems powering AI-driven applications for Proximity&rsquo;s global partners.</li>
<li>Consistent reduction in inference latency and infrastructure costs.</li>
<li>High availability and fault tolerance across production services.</li>
<li>Rapid, collaborative feature delivery with product and ML teams.</li>
Clear documentation and monitoring practices that ensure operational smoothness.<br>
<li>
</li></ul><p><b>Requirements</b></p><h3 class="jobSectionHeader"><b>
What You&rsquo;ll Need</b></h3><ul>
<li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science or a related field.</li>
<li>4&ndash;6 years of backend development experience, ideally with exposure to AI or large-scale data systems.</li>
<li>Proficiency in Java, Golang, or Python with strong coding and system design fundamentals.</li>
<li>Experience designing and scaling distributed systems at production scale.</li>
<li>Exposure to LLM inference setups (e.g., vLLM, Hugging Face Inference, Triton).</li>
<li>Strong debugging, profiling, and performance tuning skills for latency-sensitive applications.</li>
<li>Knowledge of storage systems, query optimization, and caching strategies.</li>
<li>Hands-on experience with AWS (preferred), Kafka, and CI/CD pipelines.</li>
<li>Ability to work autonomously and deliver in fast-paced environments.</li>
<li>Passion for mentoring engineers and leading by example.</li>
<li>Curiosity about ad-tech and search systems, and how to optimize them for user and business outcomes.</li>
</ul><p></p><h3 class="jobSectionHeader"><b>Success Traits</b></h3><p>
Builder&rsquo;s mindset &middot; High ownership &middot; Analytical clarity &middot; Collaborative spirit &middot; Global mindset &middot; Growth orientation</p><p><b>
Benefits</b></p><h3 class="jobSectionHeader"><b>
Why Join Proximity Works</b></h3><ul>
<li>Work directly on frontier AI problems with some of the world&rsquo;s largest sports, media, and entertainment brands.</li>
<li>Be part of a global-first, high-performance engineering culture.</li>
<li>Competitive compensation aligned with global markets, with remote-first flexibility.</li>
<li>Annual global off-sites with Proxonauts from San Francisco, Dubai, India, and beyond.</li>
<li>High autonomy, direct accountability, and the opportunity to ship AI systems at scale.</li></ul></div>

Backend Engineer - AI-Powered Search & Applications (Remote | Immediate Joiners)

Join Proximity Works and explore 2   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Proximity Works

ABOUT_COMPANY

Senior Data Scientist - LLMs, RAG & Multimodal AI (Remote | Immediate joiner)

Backend Engineer - AI-Powered Search & Applications (Remote | Immediate Joiners)