Physical Systems Modeler - 1D Simulation
The Physical Systems Modeler - 1D Simulation is responsible for building simulators and component models that generate synthetic training data, sourcing or developing first-principles models of thermofluid and electrical power systems using acausal modeling frameworks like Julia ModelingToolkit or Modelica. They will build reusable, parameterized models of HVAC and electrical equipment for trade studies, design parameter sweeps and scenario matrices that cover operating conditions including off-design and fault scenarios, validate models against real-world data by collaborating with expert engineers, calibrate simulations to manufacturer specifications or field measurements, integrate simulation outputs with ML pipelines for model training and evaluation, and build and maintain well-documented, tested component libraries that scale across equipment types and compose system-level models.
Research Scientist - Applied AI
The AI Research Scientist will lead projects developing agentic AI systems designed to solve real-world mechanical, electrical, and aerospace engineering problems that think, remember, act, and adapt. Responsibilities include applying or inventing reinforcement learning strategies for reasoning and planning in long-horizon tasks in relevant engineering environments, contributing to both research strategy and technical implementation with hands-on ownership over their applied research stream, collaborating with a small elite team of researchers and engineers across domains, and staying current with cutting-edge research to bring promising ideas into reality.
Founding Forward Deployed Research Engineer (FDRE)
FDREs work in small teams with the agility and autonomy of a startup, but with the experience and support of an established organization. They own the mission end-to-end, being the technical owner in the field, clarifying goals, shaping the plan, making hard calls, and shipping systems that move real metrics. They partner for impact by working directly with operators and executives to scope what matters most and turn it into production results. They build with research in the loop by collaborating with AI R&D on prompts, tools, and model improvements and bring back field signals to improve the next model and the platform. They convert wins into a flywheel by turning patterns into playbooks, products, and libraries to make every deployment faster, more powerful, and more reliable.
People Data & Operations Manager
Conduct original research while observing how ideas move through a high-growth startup's Go-To-Market motion to create measurable impact; work closely with Snorkel researchers on open-ended projects producing clear research outputs such as experiments, prototypes, internal writeups, and potentially publications; innovate human-AI interaction by designing new paradigms for distilling human expertise into model behavior; collaborate with leading labs to develop data strategies that enable next-generation agentic, reasoning, and multi-modal models; engage in projects including synthetic data generation and filtering, evaluation datasets and benchmarks for LLM/RAG/agent behavior, data-centric methods for improving reliability, calibration, and failure-mode coverage, and evaluating HITL data annotation processes and improvements.
Research-Hardware Codesign Engineer
The Research-Hardware Codesign Engineer is responsible for working at the intersection of model research and silicon/system architecture to shape the numerics, architecture, and technology decisions for future OpenAI silicon. Responsibilities include building on the roofline simulator to track workloads and analyze the impact of system architecture decisions, debugging discrepancies between performance simulations and real measurements with clear communication of root causes, writing emulation kernels for low-precision numerics and lossy compression schemes, prototyping numeric modules through RTL synthesis, and occasionally owning an RTL module end-to-end. The engineer will proactively bring in new machine learning workloads to prototype and evaluate opportunities or risks, understand the full scope from ML science to hardware optimization, break down objectives into near-term deliverables, facilitate cross-team collaborations, and clearly communicate design tradeoffs with supporting evidence.
Member of Technical Staff - Alignment Lead
Drive the entire alignment stack, including instruction tuning, RLHF, and RLAIF, to push the model toward high factual accuracy and robust instruction following. Lead research efforts to design next-generation reward models and optimization objectives that improve human preference performance. Curate high-quality training data and design synthetic data pipelines addressing complex reasoning and behavioral gaps. Optimize large-scale reinforcement learning pipelines for stability and efficiency, enabling rapid model iteration cycles. Collaborate closely with pre-training and evaluation teams to create feedback loops that translate alignment research into generalizable model improvements.
HR Operations Partner
Develop novel architectures, system optimizations, optimization algorithms, and data-centric optimizations that significantly improve over state-of-the-art. Take advantage of the computational infrastructure of Together to create the best open models in their class. Understand and improve the full lifecycle of building open models; release and publish insights such as blogs and academic papers. Collaborate with cross-functional teams to deploy models and make them available to a wider community and customer base. Stay up-to-date with the latest advancements in machine learning.
Senior Product Manager, Integration Agents
Develop state-of-the-art tools for correcting, improving, and enhancing written English using various NLP, ML, and DL technologies. Productize and ship these features into Superhuman's product offerings, which millions of users use daily. Stay up-to-date with the latest research trends that could improve the product. Contribute to the research strategy and technical culture of the company. Attract professionals in the industry to build a best-in-class research team that creates a state-of-the-art writing and communication assistant.
MEP Manager, Data Centers
Develop novel architectures, system optimizations, optimization algorithms, and data-centric optimizations that significantly improve over state-of-the-art. Take advantage of the computational infrastructure of Together to create the best open models in their class. Understand and improve the full lifecycle of building open models; release and publish insights through blogs, academic papers, etc. Collaborate with cross-functional teams to deploy models and make them available to a wider community and customer base. Stay up-to-date with the latest advancements in machine learning.
Researcher, Synthetic RL
As a Research Scientist on the Synthetic RL team, you will develop novel reinforcement learning techniques that use synthetic environments and feedback to improve large-scale models. You will research and develop reinforcement learning algorithms, design and run experiments to study training dynamics and model behavior at scale, and collaborate with engineers and researchers to integrate successful approaches into model training pipelines.
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