&lt;div class=&quot;content-intro&quot;&gt;&lt;p data-start=&quot;272&quot; data-end=&quot;669&quot;&gt;Glance AI is an AI commerce platform shaping the next wave of e-commerce with inspiration-led shopping, less about searching for what you want and more about discovering who you could be. Operating in 140 countries, Glance AI transforms every screen into a stage for instant, personal, and joyful discovery, where inspiration becomes something you can explore, feel, and shop in the moment.&lt;/p&gt;
&lt;p data-start=&quot;272&quot; data-end=&quot;669&quot;&gt;Its proprietary models, seamlessly integrated with Google’s most advanced AI platforms, Gemini and Imagen on Vertex AI, deliver hyper-realistic, deeply personal shopping experiences across categories such as fashion, beauty, travel, accessories, home décor, pets, and more. Designed to seamlessly integrate into everyday consumer technology, Glance AI reimagines the future of e-commerce with inspiration-led discovery and shopping.&lt;/p&gt;
&lt;p data-start=&quot;671&quot; data-end=&quot;1119&quot;&gt;With an open architecture built for effortless adoption across hardware and software ecosystems, Glance AI is creating a platform that can become a staple in everyday consumer technology. It partners with the world’s leading smartphone makers, connected TV manufacturers, telecom providers, and global brands — meeting people where they are: on mobile, smart TVs, and brand websites.&lt;/p&gt;
&lt;p data-start=&quot;671&quot; data-end=&quot;1119&quot;&gt;Through Glance AI’s rich first-party data and unparalleled consumer access, it harnesses InMobi’s global scale, insights, and targeting capabilities to create high-impact, performance-driven shopping journeys for brands worldwide. Part of the InMobi Group, a global technology and advertising leader reaching over 2 billion devices and serving more than 30,000 enterprise brands worldwide, Glance AI is backed by Google, Jio Platforms, and Mithril Capital.&lt;/p&gt;&lt;/div&gt;&lt;p&gt;&lt;strong&gt;Glance - An InMobi Group Company   &amp;nbsp;&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;Founded in 2019, Glance is a consumer technology company that operates disruptive digital platforms including Glance, Roposo, and Nostra. Glance’s ’smart lock screen’ inspires consumers to make the most of every moment by surfacing relevant experiences without the need for searching and downloading apps. Glance Lock Screen is currently available on over 450 million smartphones worldwide. Roposo is a LIVE platform that is revolutionizing live experiences, through a unique, immersive, creator-led approach. Nostra is the largest gaming platform in India and Southeast Asia, offering gamers engaging ways to discover, play, watch, learn and compete. &amp;nbsp;&amp;nbsp;&lt;br&gt;&amp;nbsp;&lt;br&gt;Headquartered in Singapore, Glance is an unconsolidated subsidiary of&amp;nbsp;InMobi&amp;nbsp;Group and is funded by Jio Platforms, Google, and Mithril Capital. For more information visit glance.com, nostra.gg, and&amp;nbsp;&lt;a href=&quot;http://roposo.com/&quot;&gt;roposo.com&lt;/a&gt;&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;What should you know about joining Glance? &amp;nbsp;&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;At Glance, we walk the talk – free yourself, dream big, and chase your passion! On joining, you’ll have opportunities to make an immediate impact on mission-critical projects, as you work with highly capable and ambitious peer groups.&amp;nbsp; &amp;nbsp;&lt;/p&gt;
&lt;p&gt;Be rewarded for your autonomy even as you collaborate. Ideate, innovate, and inspire by leveraging bleeding-edge tech to disrupt consumer experiences.&amp;nbsp; &amp;nbsp;&lt;/p&gt;
&lt;p&gt;While you work, we’ll take care of nourishing your body, mind, and soul. This includes daily meals, gym, trainings, tech tools, and regular unwind sessions. Also, feel free to bring your kids – even the furry ones – to the office!&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;What you will be doing?&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Glance&amp;nbsp;&lt;/strong&gt;is looking for a Machine Learning Engineer.&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;
&lt;ul&gt;
&lt;li&gt;
&lt;ul data-start=&quot;246&quot; data-end=&quot;1727&quot;&gt;
&lt;li data-start=&quot;246&quot; data-end=&quot;334&quot;&gt;
&lt;p data-start=&quot;248&quot; data-end=&quot;334&quot;&gt;&lt;strong data-start=&quot;248&quot; data-end=&quot;275&quot;&gt;3–6 years of experience&lt;/strong&gt; in deep learning, computer vision, or generative modeling.&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;336&quot; data-end=&quot;526&quot;&gt;
&lt;p data-start=&quot;338&quot; data-end=&quot;526&quot;&gt;&lt;strong data-start=&quot;338&quot; data-end=&quot;367&quot;&gt;Strong hands-on expertise&lt;/strong&gt; with PyTorch, HuggingFace Diffusers, and &lt;strong data-start=&quot;409&quot; data-end=&quot;448&quot;&gt;custom node development for ComfyUI&lt;/strong&gt; (including graph-based pipelines, custom schedulers, and optimization nodes).&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;528&quot; data-end=&quot;684&quot;&gt;
&lt;p data-start=&quot;530&quot; data-end=&quot;684&quot;&gt;&lt;strong data-start=&quot;530&quot; data-end=&quot;552&quot;&gt;Deep understanding&lt;/strong&gt; of diffusion processes, UNet architectures, latent space manipulation, VAE internals, and pixel-to-latent/latent-to-pixel modeling.&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;686&quot; data-end=&quot;828&quot;&gt;
&lt;p data-start=&quot;688&quot; data-end=&quot;828&quot;&gt;&lt;strong data-start=&quot;688&quot; data-end=&quot;709&quot;&gt;Proven experience&lt;/strong&gt; with &lt;strong data-start=&quot;715&quot; data-end=&quot;744&quot;&gt;LoRA / HyperLoRA training&lt;/strong&gt;, weight merging, adapter composition, and identity-preserving generative workflows.&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;830&quot; data-end=&quot;1226&quot;&gt;
&lt;p data-start=&quot;832&quot; data-end=&quot;890&quot;&gt;&lt;strong data-start=&quot;832&quot; data-end=&quot;880&quot;&gt;Experience with LLM-based agentic frameworks&lt;/strong&gt;, such as:&lt;/p&gt;
&lt;ul data-start=&quot;893&quot; data-end=&quot;1226&quot;&gt;
&lt;li data-start=&quot;893&quot; data-end=&quot;946&quot;&gt;
&lt;p data-start=&quot;895&quot; data-end=&quot;946&quot;&gt;&lt;strong data-start=&quot;895&quot; data-end=&quot;903&quot;&gt;DSPy&lt;/strong&gt; for declarative self-improving pipelines&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;949&quot; data-end=&quot;1008&quot;&gt;
&lt;p data-start=&quot;951&quot; data-end=&quot;1008&quot;&gt;&lt;strong data-start=&quot;951&quot; data-end=&quot;964&quot;&gt;LangGraph&lt;/strong&gt; for stateful, multi-step reasoning agents&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;1011&quot; data-end=&quot;1051&quot;&gt;
&lt;p data-start=&quot;1013&quot; data-end=&quot;1051&quot;&gt;&lt;strong data-start=&quot;1013&quot; data-end=&quot;1026&quot;&gt;LangChain&lt;/strong&gt; for tool orchestration&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;1054&quot; data-end=&quot;1110&quot;&gt;
&lt;p data-start=&quot;1056&quot; data-end=&quot;1110&quot;&gt;&lt;strong data-start=&quot;1056&quot; data-end=&quot;1081&quot;&gt;MCP-style agent tools&lt;/strong&gt; or structured tool-calling&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;1113&quot; data-end=&quot;1226&quot;&gt;
&lt;p data-start=&quot;1115&quot; data-end=&quot;1226&quot;&gt;&lt;strong data-start=&quot;1115&quot; data-end=&quot;1141&quot;&gt;LLM token optimization&lt;/strong&gt;, including prompt compression, context distillation, and retrieval-augmented flows&lt;/p&gt;
&lt;/li&gt;
&lt;/ul&gt;
&lt;/li&gt;
&lt;li data-start=&quot;1228&quot; data-end=&quot;1391&quot;&gt;
&lt;p data-start=&quot;1230&quot; data-end=&quot;1391&quot;&gt;&lt;strong data-start=&quot;1230&quot; data-end=&quot;1268&quot;&gt;Familiarity with multimodal agents&lt;/strong&gt; (vision-language models, tool-calling agents, retrieval agents) and vector databases like &lt;strong data-start=&quot;1359&quot; data-end=&quot;1390&quot;&gt;Pinecone / FAISS / Vector Search&lt;/strong&gt;.&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;1393&quot; data-end=&quot;1564&quot;&gt;
&lt;p data-start=&quot;1395&quot; data-end=&quot;1564&quot;&gt;&lt;strong data-start=&quot;1395&quot; data-end=&quot;1435&quot;&gt;Exposure to MLOps &amp;amp; infra automation&lt;/strong&gt;, including Docker, Kubernetes (GPU workloads), Terraform, ArgoCD, CI/CD pipelines, and cloud-based scaling for gen-AI workloads.&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;1566&quot; data-end=&quot;1727&quot;&gt;
&lt;p data-start=&quot;1568&quot; data-end=&quot;1727&quot;&gt;&lt;strong data-start=&quot;1568&quot; data-end=&quot;1578&quot;&gt;Bonus:&lt;/strong&gt; Contributions to open-source diffusion pipelines, LoRA or HyperLoRA repositories, ComfyUI nodes, or agentic frameworks (DSPy, LangGraph, LangChain).&lt;/p&gt;
&lt;/li&gt;
&lt;/ul&gt;
&lt;/li&gt;
&lt;/ul&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;h3 data-start=&quot;1896&quot; data-end=&quot;1926&quot;&gt;&lt;strong data-start=&quot;1900&quot; data-end=&quot;1926&quot;&gt;What We’re Looking For&lt;/strong&gt;&lt;/h3&gt;
&lt;ul data-start=&quot;1927&quot; data-end=&quot;2586&quot;&gt;
&lt;li data-start=&quot;1927&quot; data-end=&quot;2017&quot;&gt;
&lt;p data-start=&quot;1929&quot; data-end=&quot;2017&quot;&gt;3–6 years of experience in &lt;strong data-start=&quot;1956&quot; data-end=&quot;2014&quot;&gt;deep learning, computer vision, or generative modeling&lt;/strong&gt;.&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;2018&quot; data-end=&quot;2133&quot;&gt;
&lt;p data-start=&quot;2020&quot; data-end=&quot;2133&quot;&gt;Strong hands-on expertise with &lt;strong data-start=&quot;2051&quot; data-end=&quot;2062&quot;&gt;PyTorch&lt;/strong&gt;, &lt;strong data-start=&quot;2064&quot; data-end=&quot;2089&quot;&gt;HuggingFace Diffusers&lt;/strong&gt;, and &lt;strong data-start=&quot;2095&quot; data-end=&quot;2130&quot;&gt;ComfyUI custom node development&lt;/strong&gt;.&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;2134&quot; data-end=&quot;2236&quot;&gt;
&lt;p data-start=&quot;2136&quot; data-end=&quot;2236&quot;&gt;Solid understanding of &lt;strong data-start=&quot;2159&quot; data-end=&quot;2233&quot;&gt;diffusion processes, UNet architectures, and latent space manipulation&lt;/strong&gt;.&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;2237&quot; data-end=&quot;2317&quot;&gt;
&lt;p data-start=&quot;2239&quot; data-end=&quot;2317&quot;&gt;Proven experience designing and orchestrating agentic LLM pipelines leveraging &lt;strong&gt;DSPy&lt;/strong&gt;, &lt;strong&gt;LangGraph&lt;/strong&gt;, &lt;strong&gt;tool&lt;/strong&gt; calling, and retrieval-augmented reasoning.&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;2318&quot; data-end=&quot;2403&quot;&gt;
&lt;p data-start=&quot;2320&quot; data-end=&quot;2403&quot;&gt;Exposure to &lt;strong data-start=&quot;2332&quot; data-end=&quot;2360&quot;&gt;MLOps &amp;amp; infra automation&lt;/strong&gt; (Docker, Kubernetes, Terraform, ArgoCD).&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;2404&quot; data-end=&quot;2514&quot;&gt;
&lt;p data-start=&quot;2406&quot; data-end=&quot;2514&quot;&gt;Familiarity with &lt;strong data-start=&quot;2423&quot; data-end=&quot;2444&quot;&gt;multimodal agents&lt;/strong&gt;, &lt;strong data-start=&quot;2446&quot; data-end=&quot;2459&quot;&gt;LangChain&lt;/strong&gt;, or &lt;strong data-start=&quot;2464&quot; data-end=&quot;2501&quot;&gt;vector databases (Pinecone/FAISS/Vector Search)&lt;/strong&gt; is a plus.&lt;/p&gt;
&lt;/li&gt;
&lt;li data-start=&quot;2515&quot; data-end=&quot;2586&quot;&gt;
&lt;p data-start=&quot;2517&quot; data-end=&quot;2586&quot;&gt;Bonus: Contributions to open-source diffusion or LoRA repositories / Agentic systems.&lt;/p&gt;
&lt;/li&gt;
&lt;/ul&gt;
&lt;/li&gt;
&lt;/ul&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;p&gt;&lt;span class=&quot;ui-provider ee bcu auz bcv bcw bcx bcy bcz bda bdb bdc bdd bde bdf bdg bdh bdi bdj bdk bdl bdm bdn bdo bdp bdq bdr bds bdt bdu bdv bdw bdx bdy bdz bea&quot;&gt;&quot;&lt;em&gt;Glance collects and processes personal data such as your name, contact details, resume and other information that may contain personal data for the purpose of processing your application. Glance utilizes Greenhouse, a third-party platform. Please review Greenhouse&#39;s Privacy Policy to understand how the data collected from you is processed and managed. By clicking on &#39;Submit Application&#39;, you acknowledge and agree to the above privacy terms. Should you have any privacy concerns, you may contact us through the details mentioned in your application confirmation email.&quot;&lt;/em&gt;&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;

Machine Learning Engineer II - Computer Vision

Glance Careers - (Machine Learning Engineer II - Computer Vision)

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Machine Learning Engineer II - Computer Vision

Glance Careers - (Machine Learning Engineer II - Computer Vision)

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