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Application Deadline: 09/12/2026 Address: 33 Dundas Street West Job Family Group: Technology BMO is seeking a Machine Learning Developer to join our team in Toronto. This role is ideal for an early-career professional…
About Ancestry: When you join Ancestry, you join a human-centered company where every person’s story is important. Ancestry®, the global leader in family history, connects everyone with their past so they can discover,…
The Opportunity Join Adobe's AI Foundations team within the Search, Discovery & Content AI (SDC) organization and help build the next generation of AI-powered retrieval, matching, ranking, and content…
Senior Application Engineer Location: On-Site - Dayton At Parallax, we believe in advancing science and serving the public good—and we’re looking for team members who do too. If you’re ready to support big ideas…
Machine Learning Engineer on Apple's ML Platform Technology team, building large-scale ML systems and data curation infrastructure that power Apple Intelligence and foundation models behind Siri, Search, Music, and other services. Work focuses on optimizing multi-billion-parameter language, vision, and speech models for production-scale serving using frameworks like PyTorch, TensorFlow, or JAX.
Machine Learning Research Engineer who builds ML systems to predict protein functionality and accelerate food-science R&D, plus applies AI (agents, internal tools) across the company. Core stack: Python with PyTorch/JAX/TensorFlow, and methods like protein representation learning, graph/geometric deep learning, generative/diffusion models, active learning, and Bayesian optimization.
A Member of Technical Staff on the AI Training Platform builds and scales the infrastructure used to train, evaluate, and benchmark models — including multi-node distributed training, the proprietary training framework, and CUDA/Triton kernel optimization — to help researchers map neural networks onto the company's novel physics-based compute hardware.
A hybrid technical/commercial role owning enterprise customer relationships for Fireworks AI's inference platform — from scoping pilots and onboarding through production deployment, technical escalations, QBRs, and renewals/expansions. Core tech: APIs, AWS/GCP/Azure, and production LLM work (prompting, fine-tuning, RAG).
Build and deploy deep learning models for space-based electro-optical image processing to support defense and intelligence missions.
A senior engineer who designs and runs large-scale distributed production systems powering Xero's AI features for millions of users, owning architecture, tech debt, and mentoring. Core stack is Python, SQL, Spark/Dask, AWS, and Kubernetes, with a focus on productionizing ML and LLM features alongside Applied Scientists.
About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and…
Senior Technical Evangelist for Pure Storage's AI platform, turning its data platform tech (Portworx, Evergreen//One, Data Stream Services) into technical content, sandbox demos, reference architectures, and sales enablement. Requires deep AI-stack skills (PyTorch, vLLM, Kubernetes, RAG, vector DBs) plus Python/shell scripting, working in-office in Santa Clara or Bellevue.
Build and scale the machine-learning infrastructure that powers Quince’s AI-driven retail platform, designing training pipelines, feature stores, and real-time inference systems on AWS and Kubernetes.
Remote (US) Senior Data Engineer at Octave, a behavioral health company, building and evolving its modern data stack and the foundation of its AI/ML platform. Day to day: designing scalable ingestion, transformation, and storage pipelines with SQL/Python and GCP/AWS tooling, and enabling end-to-end ML workflows with data scientists.
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify…
Leads AI/ML-driven physical design flows for semiconductor IP, optimizing RTL-to-GDS methodologies to improve performance, power, and area (PPA) and runtime across advanced nodes.
Develops and optimizes high-performance C++ components for training machine learning models on custom silicon, working closely with compiler and kernel teams to scale AI workloads efficiently.
Develops and optimizes AI models (LLMs/vision) for custom hardware, tuning performance and accuracy across software, compiler, and hardware layers.
Develops and leads an AI compiler (TT-Forge) using MLIR, optimizing graph transformations and kernel-level passes for high-performance AI workloads across hardware/software stacks.
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