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Build and deploy AI/ML models and tools to accelerate drug discovery and decision-making in a global biopharma company, partnering with scientists and engineers.
Develops and maintains Java-based mission-critical software in Linux environments, focusing on RESTful APIs, JSON/XML data processing, and application modernization for government contracts.
Leads development of machine vision software for research science, focusing on behavior annotation tools on the Envision platform; collaborates with scientists and stakeholders to design, implement, and deploy high-quality bioinformatics applications while mentoring team members and driving technical innovation.
Build and ship recommendation models that power a personalized shopping feed, using ML to learn user taste from sparse signals and scale across millions of products.
Leads AI/ML engineering for BlackRock’s asset management, designing and deploying generative AI, predictive modeling, and optimization systems at scale in production environments.
This role involves leading the design and deployment of production-grade AI and machine learning systems, including generative AI and intelligent agents, to support BlackRock's asset management operations. The engineer will build scalable AI platforms and infrastructure while collaborating with cross-functional teams to drive technical strategy.
The Algorithm Engineer will design, optimize, and deploy deep learning and generative AI models for image processing and computer vision applications within semiconductor process control. The role involves the full project lifecycle, focusing on model performance, efficiency, and deployment using frameworks like PyTorch or TensorFlow.
Stanford University is seeking a Machine Learning Engineer to perform advanced technical research for the ARPA-H/BDF grant. The grant required use of AI and ML tools for modeling and building biomedical applications…
This role involves building and optimizing OpenAI's inference stack for AWS Trainium hardware. The engineer will work across the stack, including developing high-performance kernels, improving compiler support, and optimizing model execution for frontier-scale AI systems.
Build and maintain enterprise-scale Java applications using Spring and REST APIs, collaborating with U.S. teams on mission-critical systems.
Member of Technical Staff - ML Performance About Us Veeda AI is building the next generation of multimodal foundation world models for Physical AI. We're a small, fast-moving team of engineers and researchers from…
Leads technical delivery of confidential compute projects, bridging global clients, internal engineering, and operations to deploy high-performance accelerators in cloud/on-prem environments for mission-critical workloads.
Builds and maintains the infrastructure for AI-native email triage systems, focusing on model training, deployment, inference, and observability to ensure scalable, low-latency AI workflows.
Data Scientist building an in-house coupled simulation framework for dense plasma focus fusion machines, including radiation models, surrogate models, and data pipelines for shot diagnostics—primarily using Python (NumPy, SciPy, JAX/PyTorch) with C++/Fortran as needed.
Forward Deployed Engineers at Baseten work directly with major AI companies, owning technical outcomes for AI models including inference and post-training systems. They act as technical leads, debug production issues, and contribute to product development across multiple client accounts.
As a Machine Learning Research Engineer at RBC Borealis, you’ll build ML-based software solutions, collaborate with stakeholders, prototype algorithms, and integrate them into products using Python 3.x, PyTorch, JAX, or Tensorflow, focusing on generative AI, NLP, and time series analysis.
An AI/ML Engineer at Nexstar Media Group designs, builds, and deploys machine learning and agentic AI systems for real-world products, working across the full ML lifecycle from data preparation to model monitoring and iteration.
Build and deploy reinforcement learning policies for a humanoid robot platform, iterating directly on physical hardware and closing the sim-to-real gap.
NVIDIA is seeking Ph.D. students for research internships focused on generative AI, including multimodal models, diffusion models, and large language models. Interns will design algorithms, collaborate with research teams, and contribute to prototypes or publications while working with advanced AI technologies.
The Deep Learning Performance Architect will analyze and optimize performance for LLM workloads on NVIDIA's hardware architectures. This role involves developing analytical models and collaborating with software and hardware teams to influence the design of next-generation inference products.
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