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Senior DevOps ML Engineer builds and runs AI platforms, splitting time between GPU-accelerated Kubernetes, backend services, and MLOps to productionize LLMs and digital avatars.
Build and optimize high-performance inference APIs and ML features for generative AI models running on custom hardware using Python, PyTorch, and C++.
Build and optimize high-performance inference APIs and tools for generative AI models using Python, PyTorch, and C++ on Cerebras’ custom hardware.
Backend engineer at a GenAI startup building scalable Go/Python systems for AI-powered avatar and video generation, serving millions of creators.
Build and optimize real-time streaming systems for AI-powered computer vision products like anomaly detection and human pose estimation using C++/Python and NVIDIA stacks.
Build and deploy computer-vision models that detect liveness spoofs and deepfakes to secure VIDA’s identity-verification pipeline using PyTorch and OpenCV.
Build and fine-tune large language models for Avito’s products, optimizing training pipelines and inference speed for production-scale NLP systems.
Build and deploy real-time computer-vision models for a neural-interface medical device that translates brain intent into action, optimizing models for wearable hardware and clinical readiness.
Lead a team of data scientists to build ML models that classify and sort recycled plastics in real time using spectral sensor data and deep learning.
Build and scale face-recognition systems using PyTorch/TensorFlow, own end-to-end ML pipelines on AWS, and lead fairness analysis for biometric models in production.
Build and optimize production-grade face biometrics and identity-verification systems using deep learning and computer vision, focusing on liveness detection, anti-spoofing, and fraud prevention.
Principal engineer leading backend and ML infrastructure at a Series C conversational AI company, designing real-time data pipelines, scaling GPU fleets, and optimizing inference costs for enterprise speech/NLP systems.
Optimize inference for local LLMs and internal models using vLLM/Triton, manage GPU resources, and monitor high-load AI infrastructure for a logistics-focused AI company.
Design and deploy scalable, real-time AI systems including LLM inference pipelines, RAG, and vector databases using Python, TensorFlow/PyTorch, and Kubernetes.
About * Who we are Video is 90% of the world's data. Most of it is invisible to machines. TwelveLabs builds the intelligence layer to change that. Our multimodal AI models understand video the way humans do —…
Build and optimize the production serving stack for Jockey Core, TwelveLabs’ reasoning LLM that powers agentic video understanding across millions of hours of content.
Build and maintain full-stack apps integrating AI modules (RAG, agents) using React, Node.js, and Python; design scalable APIs, manage data pipelines, and deploy on cloud.
Build and scale SpaceXAI’s high-throughput API in Rust/C++ to serve AI models globally with low latency, handling billions of tokens per minute.
Principal Data Engineer builds and leads the AI data stack for Anaplan’s LLM and agentic systems, designing retrieval layers, vector/graph databases, and real-time GenAI features for enterprise planning workflows.
Principal Data Engineer builds and leads AI systems at Anaplan, designing retrieval layers, RAG pipelines, and GenAI features that integrate LLMs into real-time planning workflows.
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