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Cellanome is hiring a Machine Learning Engineer to design and optimize algorithms for data analysis and workflow automation on its biology instrumentation platform. The role blends computer vision, signal processing, and classical/AI-ML methods in Python, with deployment on edge devices, GPUs, and HPC environments.
Build AI agents and LLM-driven workflows for a reactor-construction OS used by teams deploying next-gen nuclear plants, shipping models and features to production.
Build AI features and agents for a nuclear-energy startup’s operating system, shipping models for site evaluation, scheduling, and anomaly detection used by reactor construction teams.
Build AI agents and LLM-driven features for NOS, the AI platform that powers next-gen nuclear reactor construction, including retrieval, evals, and time-series models.
What you get to do in this role We are looking for a Senior Manager of Machine Learning Engineering to lead a team building the next generation of AI Search and Retrieval capabilities that power intelligent experiences…
Founding engineer at a pre-seed AI recruiting marketplace who owns the AI/ML intelligence layer end to end — recommendation, ranking, and LLM-powered matching — plus the production data pipelines that run them, shipping daily from San Francisco. Core stack: TypeScript or Python, LLM APIs, and optionally React, Supabase, Prisma, and vector search.
Senior Technical Recruiter at Together AI who partners with AI Research and Engineering leadership to run full-cycle hiring of researchers, research engineers, and ML systems talent — building pipelines from academia and industry, designing research-specific interview loops, and advising leaders on AI talent markets.
Staff ML engineer who owns the model-serving layer of Together AI's Voice AI platform — optimizing STT, TTS, and speech-to-speech inference (Whisper, Parakeet, Orpheus, Kokoro) on H100/H200/B200 GPUs with engines like TRT-LLM and SGLang, plus building batching, profiling, and evaluation frameworks. On-site in San Francisco.
Together AI is hiring a Senior ML Engineer to own the model-serving layer of its Voice AI platform in San Francisco — optimizing real-time speech-to-text, text-to-speech, and speech-to-speech inference on GPUs using engines like TensorRT-LLM and SGLang. Day to day: latency/throughput tuning, streaming audio batching, and building model evaluation frameworks.
Machine Learning Engineer on Together AI's Inference Engine team, building and optimizing production systems that run large language model inference at scale. Day-to-day work centers on Python and PyTorch, high-performance runtime services, and low-level systems optimization (memory, threading, CUDA/Triton kernels).
Staff Software Engineer on Addepar's Reference Data team in Edinburgh, building and productionizing AI-native products for its wealth/investment platform — architecting LLM pipelines, agentic frameworks, and agent capabilities (MCP, tool use) and hardening them into scalable production services.
Du willst in einem jungen Tech-Team arbeiten und begeisterst Dich für KI, LLM und RAG für industrielle Einsatzzwecke? Dann werde Teil unseres Machine Learning Expert Teams und hilf uns dabei, Spezialwissen über…
Builds and optimizes AI-powered advertising systems using Grok models for candidate selection, ranking, auctions, and campaign optimization in a high-throughput, revenue-driving role.
Builds and optimizes AI-powered recommendation systems for a platform used by 600M monthly users, focusing on ranking algorithms, search, and scalable ML pipelines.
A 12-week summer 2027 internship on Coinbase's Machine Learning team in San Francisco (hybrid), where the intern owns a research-to-production project building and deploying ML models and pipelines for platform security, personalization, and crypto use cases using PyTorch/TensorFlow and production-quality Python.
Develops advanced deep learning models for audio processing on embedded devices, optimizing quality and efficiency while experimenting with novel neural architectures and research innovations.
Senior AI engineer on Apple's System RF Smart Data Ecosystem team, architecting and deploying internal generative-AI and multi-agent systems that automate hardware engineering tasks and analyze wireless design/manufacturing data. Core stack: Python (async), FastAPI/Flask, agent frameworks (MCP, A2A), and multi-provider LLMs.
Senior ML engineer builds and deploys scalable AI pipelines for materials, chemistry and physical sciences, using PyTorch, cloud infra and production-grade MLOps.
Summer 2027 internship (10-12 weeks, on-site in Austin, TX) at defense startup Allen Control Systems, working alongside engineers on real-time computer vision for the Bullfrog counter-drone system — detecting and tracking aerial threats, building training data pipelines, and getting models to run on embedded hardware like NVIDIA Jetson using Python/PyTorch.
Build and integrate core AI capabilities into a secure enterprise platform, deploying foundation models and optimizing scalable ML systems for reliability and performance.
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