AI Research Engineer Specializing in Language Models

Position OverviewJoin our innovative team at Nace.ai as we push the boundaries of artificial intelligence through cutting-edge research in large language models (LLMs) and vision-language models (VLMs). We are in search of a talented AI Research Engineer with a strong focus on adaptive learning methodologies, including meta-learning and hypernetworks. Your r…

At GenBio AI, we are pioneering the development of multiscale foundation models aimed at decoding and simulating human biology. Our vision is to empower scientists to tackle some of humanity's most significant challenges in drug discovery, healthcare, and fundamental research through our innovative AIDO (AI-Driven Digital Organism) framework, which facilitates the prediction, simulation, and programming of biological systems across various scales. We are laying the groundwork for this ambitious future by engineering virtual cells that model and simulate the fundamental unit of life.Our team is composed of a diverse and talented group of product-focused researchers and engineers who are committed to making this vision a reality. We take pride in our robust engineering culture, which fosters interdisciplinary collaboration. Headquartered in Palo Alto, we also have satellite offices in Paris and Abu Dhabi.In your role as an AI Engineer, you will develop AI scientists capable of performing autonomous biomedical research utilizing GenBio’s virtual instruments and simulators. Your successful contributions will play a crucial role in rapidly designing and orchestrating comprehensive biological simulation studies aimed at drug design, healthcare innovations, and biotechnology advancements.

AI Research Engineer, World ModelsPalo Alto, CA (On-site)About 1XAt 1X, we are pioneering the development of humanoid robots designed to collaborate with humans, addressing labor shortages and fostering abundance across various industries.The RoleAs an AI Research Engineer specializing in world models, you will create expansive multi-modal generative models that project future sensor inputs and robotic actions derived from historical data. These foundational models empower robots to comprehend and navigate complex real-world environments. Your responsibilities will span data engineering, model architecture, and deployment, with the goal of enhancing robot autonomy. This position merges innovative research with pragmatic product development, challenging the boundaries of robotic intelligence.

At Rhoda AI, we are pioneering the development of a comprehensive foundation for the next generation of humanoid robots. Our approach integrates high-performance, software-defined hardware with advanced models and world models that facilitate their operation. Our robots are engineered to function as generalists, adept at navigating complex, real-world environments and managing previously unseen scenarios. We are at the forefront of large-scale learning, robotics, and systems research, supported by a diverse team of experts from prestigious institutions including Stanford, Berkeley, and Harvard. With over $400 million raised, we are committed to investing in the R&D, hardware innovation, and manufacturing scale-up necessary to bring our vision to life.We invite applications for the position of Research Engineer, where you will collaborate closely with our research team on comprehensive model development. This hands-on role encompasses the entire stack: data management, infrastructure, model training, and deployment. You will play a critical role in transforming research concepts into scalable, operational systems, including the learning and application of world models for planning, prediction, and control.Key ResponsibilitiesDesign and develop foundational and world models for extensive robotic learning.Establish and manage data pipelines encompassing collection, curation, filtering, and augmentation for multimodal robotic data (vision, proprioception, actions, language, video).Engage in pre-training and post-training processes, including fine-tuning, alignment, and evaluation of large models and world models.Implement and experiment with various model architectures.Create training and evaluation frameworks for world models, focusing on rollout quality, long-horizon predictions, and downstream task performance.Enhance training infrastructure and workflows (distributed training, efficiency, debugging).Collaborate closely with researchers to convert ideas into resilient, scalable implementations.Assist with experiments, ablations, and real-world deployments on robotic systems.QualificationsProficiency in software engineering combined with a research-driven mindset.Demonstrated experience in implementing ML models end-to-end, beyond merely executing existing code.Comprehensive understanding of the entire ML pipeline: data → pre-training → post-training → evaluation → deployment.Strong foundation in deep learning frameworks and methodologies.Ability to work collaboratively in a fast-paced, innovative environment.

At Rhoda AI, we are pioneering the development of a comprehensive platform for the next generation of humanoid robots. Our ambition encompasses everything from high-performance, software-defined hardware to the foundational models and video world models that govern their operations. Our robots are engineered as versatile generalists, adept at navigating intricate, real-world environments and addressing scenarios that are not encountered during training. We operate at the confluence of large-scale learning, robotics, and systems, with a research team that includes esteemed researchers from Stanford, Berkeley, Harvard, and other renowned institutions. Rather than merely enhancing a feature, we are constructing an entirely new computing platform dedicated to physical tasks. With over $400M raised, we are aggressively investing in research and development, hardware innovation, and scaling up manufacturing to realize this vision.Key ResponsibilitiesLead research initiatives focused on foundational models and world models for robotics, including representation learning, dynamics/prediction, planning, and control.Define research challenges and formulate hypotheses rooted in real-world robotic autonomy requirements.Design and execute rigorous experiments at scale, encompassing ablations, benchmarking, and evaluation methodologies.Develop and assess model architectures aimed at enhancing long-horizon predictions, rollout quality, and overall robotic task performance.Investigate and improve pre-training and post-training processes, including fine-tuning, alignment, and evaluation of large multimodal models.Collaborate closely with Research Engineers to translate innovative ideas into scalable training pipelines and dependable systems.Effectively communicate research findings through internal documentation, presentations, and reviews.Publish and present research at prestigious venues.Required QualificationsPh.D. in a relevant discipline such as Machine Learning, Robotics, Computer Science, Electrical Engineering, Applied Mathematics, or Computer Vision.Demonstrated strong publication record in high-quality research (e.g., NeurIPS, ICML, ICLR, CoRL, RSS, ICRA, CVPR).In-depth knowledge of current machine learning techniques, particularly in areas such as:Deep learning and representation learning.Sequence modeling and transformers.Generative modeling (e.g., diffusion, autoregressive, latent-variable models).

AI Research Engineer specializing in Reinforcement Learning | AI & RoboticsLocation: Palo Alto, CA (on-site)About 1XAt 1X, we are pioneering the development of humanoid robots that collaborate with humans to address labor shortages and foster abundance in various industries.The RoleAs an AI Research Engineer with a focus on Reinforcement Learning, you will play a vital role in enhancing NEO's capabilities through advanced RL algorithms. This position involves working in both simulated and real-world environments to create robust behaviors and implement them within home settings. Your contributions will be crucial in increasing the safety, efficiency, and versatility of our robotic systems.

Join the OPPO Research Center as a forward-thinking NLP Research Scientist, where you will play a pivotal role in shaping our next-generation AI hardware platforms, including innovative AI Glasses and Earphones. Your passion for generative AI research will drive the design, training, and deployment of sophisticated multimodal intelligence models that effortlessly merge language, vision, and action. Collaborating within our dynamic team, you will co-create algorithms and hardware, translate groundbreaking research into tangible products, and contribute your findings to prestigious AI conferences.

Ricursive Intelligence is at the forefront of AI innovation, dedicated to developing self-enhancing systems with a strong emphasis on chip design. Our mission is to transform chip development and create a seamless connection between artificial intelligence and the hardware that powers it, thereby accelerating the journey towards artificial superintelligence.We are on the lookout for top-tier researchers to engage in groundbreaking AI research, tackling a diverse array of challenges associated with LLM modeling, training, data management, evaluation, and beyond. As a dynamic startup, our team is highly collaborative and hands-on; researchers are empowered to design and execute large-scale experiments and to build and deploy models in a production environment.

At Inflection AI, we are dedicated to leveraging the transformative capabilities of artificial intelligence to enhance human well-being and productivity.The future of AI will be characterized by agents we can trust to act on our behalf.We are at the forefront of this evolution with our human-centric AI models that integrate emotional intelligence (EQ) with cognitive intelligence (IQ), shifting interactions from mere transactions to meaningful relationships, thereby generating lasting value for individuals and organizations alike.Our initiatives manifest in two primary forms:Pi, your personal AI, designed to be a compassionate companion that enriches everyday life through practical support and insights.Platform — large language models (LLMs) and APIs that empower developers, agents, and enterprises to infuse Pi-level emotional intelligence into experiences where empathy and understanding are crucial.We are building towards a future of AI agents that foster trust, enhance understanding, and create aligned, long-term value for everyone.About the RoleAs a Model Training Engineer, you will be responsible for designing, building, and scaling post-training pipelines that transform general LLMs into brand-fluent, production-ready assistants. Your innovations in fine-tuning and preference optimization techniques (RLHF, DPO, GRPO, RLAIF) will significantly enhance reliability, alignment, and cost-effectiveness.

About the Arc Institute The Arc Institute is an innovative scientific research organization dedicated to conducting groundbreaking basic science and technology development focused on understanding and treating complex human diseases. Based in Palo Alto, California, we operate independently while collaborating with leading institutions such as Stanford University, UCSF, and UC Berkeley. We believe that advancing scientific research requires new institutional models. Our approach includes: Comprehensive Funding: We fully finance our Core Investigators’ research teams, freeing them from the traditional constraints of project-based external grants. Advanced Technology: Recognizing the growing complexity of biomedical research, our Technology Centers develop, optimize, and deploy cutting-edge experimental and computational technologies in partnership with our Core Investigators. Exceptional Support: We provide unparalleled operational, financial, and scientific support, enabling researchers to undertake ambitious, high-risk projects aimed at significant advancements in curing diseases such as neurodegeneration, cancer, and immune dysfunction. Cultivating a Positive Culture: We prioritize a research environment that nurtures scientific curiosity, a commitment to truth, broad ambition, and collaborative spirit. Having grown to over 350 staff with more than $650 million in committed funding and a state-of-the-art lab facility, the Arc Institute is poised for rapid expansion in the coming years. About the Position The Zhou Lab is seeking passionate, diligent, and inquisitive candidates. Our specialization lies in single-cell epigenomic modeling, utilizing high-throughput single-cell multiomic technologies and computational models to investigate the spatiotemporal dynamics of gene regulation. The chosen applicant will be pivotal in pushing the boundaries of generative AI applications in biology, focusing on DNA sequences, gene regulation, and perturbation modeling. You will be tasked with developing machine learning models tailored for biological data by leveraging innovative ML architectures, interpretability techniques, and more. Furthermore, your models will be applied to significant computational biology tasks, including genome mining and molecular interaction analysis.

At code-metal, we are on a mission to revolutionize hardware deployment by matching the rapid pace of software development. Our innovative work focuses on automatic code transpilation and optimization for diverse hardware applications.As an AI Research Engineer, you will work alongside a dynamic team of researchers, tackling groundbreaking projects in generative AI and reinforcement learning.Core Responsibilities:Independently design, execute, and analyze complex experiments.Contribute to the development of core models and frameworks.Generate high-quality datasets, both real-world and synthetic.Conduct literature reviews and implement cutting-edge techniques from research papers.Engage in the publication process and present findings at conferences and workshops.Research Areas of Interest:Our current and near-term research focuses include:Contrastive representation learningSteerability and guided decodingTractable probability modelsCode-specific architecturesLLM fine-tuning, post-training, RLHF

AI Research Engineer, Scaling | InfrastructureLocation: Palo Alto, CA (on-site)At 1X, we are pioneering the development of humanoid robots designed to collaborate with humans, addressing labor shortages and fostering abundance across various sectors.The Role: As an AI Research Engineer specializing in Scaling, you will be responsible for architecting and implementing robust infrastructure that facilitates large-scale training, evaluation, and deployment for our fleet of robots. Your contributions will be essential in transitioning experimental systems into production-ready platforms, optimized for throughput, latency, and overall performance in both datacenter and edge environments. This role will significantly impact the efficiency of learning and inference processes, directly influencing the capabilities of our general-purpose humanoid robots.

At genbio, a cutting-edge start-up based in Silicon Valley, we unite visionary scientists, engineers, and entrepreneurs who are passionate about reshaping biology and medicine with the innovative potential of generative AI. Our team is comprised of leading experts and trailblazers in AI and biological sciences, continually striving to push the frontiers of what's achievable. We are the dreamers who are re-envisioning the future of biology and medicine.Our mission is to comprehensively decode biological processes, paving the way for transformative health solutions. As pioneers in pan-modal Large Biological Models (LBM), we are at the forefront of a new era in biomedicine, where our LBM training is catalyzing groundbreaking advancements and reshaping healthcare. With a robust R&D team and a leadership role in LLMs and generative AI, we are well-positioned to make a significant global impact. Join us on this exciting journey as we redefine the future of biology and medicine through the transformative power of Generative AI.

About UsOdyssey is an innovative AI laboratory at the forefront of developing general-purpose world models. These advanced multimodal intelligence systems are set to revolutionize consumer, enterprise, and intelligence applications. With models like Odyssey-2 Pro, we are pioneering the next significant leap in AI technology.Position OverviewWe are in search of passionate engineers who excel in the art of building robust systems. You should possess the ability to write elegant, scalable machine learning code, with a strong emphasis on performance and an understanding of the underlying research. You are comfortable navigating the realms of modeling and systems, boldly tackling complex technical challenges while taking pride in constructing the infrastructure and tools that enable groundbreaking advancements.Your ResponsibilitiesDevelop and scale the training and inference systems that drive Odyssey’s general-purpose world models, encompassing large-scale distributed pipelines and real-time optimization.Collaborate closely with researchers to prototype novel architectures, enhance model performance, and transition concepts from research to production.Create high-performance data and computation systems for video generation and control, facilitating rapid iteration and effective resource utilization.Design tools, metrics, and visualizations that provide insights into model behavior and evolution.Work hand-in-hand with product engineers to incorporate Odyssey’s models into real-time, interactive user experiences that exemplify new general-purpose world models.Embrace a fast-paced iterative approach. As part of a tightly-knit team, your experiments will evolve into demos and ultimately into products.Contribute to shaping Odyssey’s engineering culture, which is pragmatic, research-oriented, and always focused on what is possible next.Your ProfileA staff-level or senior engineer experienced in large-scale machine learning systems, distributed training, performance optimization, or model deployment.Hands-on and technically adept: you thrive on writing code, optimizing processes, and enhancing system efficiency.Proven experience with data structures, algorithms, and coding practices that lead to high-performance outputs.

About Mistral AIAt Mistral AI, we harness the transformative power of artificial intelligence to streamline tasks, save valuable time, and foster enhanced creativity and learning. Our innovative technology is crafted to effortlessly integrate into everyday work environments.We are committed to democratizing AI by offering high-performance, optimized, open-source models, products, and solutions. Our extensive AI platform caters to both enterprise and individual needs, featuring products like Le Chat, La Plateforme, Mistral Code, and Mistral Compute—creating cutting-edge intelligence accessible to all users.As a vibrant and collaborative team, we are driven by our passion for AI and its potential to revolutionize society. Our diverse workforce excels in competitive settings and is dedicated to fostering innovation. With teams distributed across France, the USA, the UK, Germany, and Singapore, we pride ourselves on our creativity, humility, and team spirit.Join us in shaping the future of AI at a pioneering company. Together, we can create a lasting impact. Discover more about our culture at https://mistral.ai/careers.Role OverviewAbout the Research Engineering TeamThe Research Engineering team operates across Platform (shared infrastructure & clean coding practices) and Embedded (integrated within research squads). Our engineers have the flexibility to navigate the research↔production spectrum as their interests and needs evolve.As a Machine Learning Research Engineer, you will be responsible for building and optimizing large-scale learning systems that underpin our open-weight models. Collaborating closely with Research Scientists, you may join either:- Platform RE Team: Focus on enhancing our shared training frameworks, data pipelines, and tools utilized across all teams; or- Embedded RE Team: Become part of a research squad (Alignment, Pre-training, Multimodal, etc.) to turn innovative ideas into scalable, repeatable code.Key Responsibilities• Support researchers by managing the complex aspects of large-scale ML pipelines and developing robust tools.• Bridge cutting-edge research with production: integrate checkpoints, optimize evaluations, and create accessible APIs.• Conduct experiments utilizing the latest deep-learning techniques (sparsification on 70B+ models, distributed training across thousands of GPUs).• Design, implement, and benchmark ML algorithms; produce clear and efficient code in Python.• Deliver prototypes that evolve into production-grade components for Le Chat and our enterprise API.

Technical Staff Member - Foundation Model Architecture & AI InfrastructureJoin Vinci, a leading innovator in operator intelligence infrastructure for cutting-edge hardware programs. We have successfully demonstrated that a single foundation model can seamlessly operate across various industries on complex production workloads.Leveraged over 45TB of structured physics data for training.Facilitated billion-voxel inference in live production settings.Implemented within Tier-1 semiconductor and hardware environments.Adapted to operate across diverse physical scales and operator regimes.This is not just a research prototype; it is a robust production infrastructure. We are now on a mission to scale our deployment to industrial levels:Enhancing simulation throughput by two orders of magnitude.Transitioning from billion-voxel to trillion-voxel domains.Broadening operator coverage to nonlinear regimes.Enabling global, multi-entity deployments within Tier-1 ecosystems.Our goal is not merely to become a frontier AI lab but to establish the default operator intelligence layer that hardware companies depend on.The Operator FrontierOur unified model currently addresses a subset of partial differential equations within real industrial environments. The next step involves extending this unified architecture across operator systems, including:Maxwell’s equationsElasticityPlasticityNavier–StokesNonlinear constitutive systemsCoupled multiphysics interactionsWe aim to evolve a single operator foundation model that generalizes across industries, physical scales, and conditioning regimes, all while scaling in deployment volume.Key ResponsibilitiesThis position focuses on AI architecture and systems engineering rather than low-level GPU kernel development. You will play a crucial role in defining and enhancing the core operator intelligence layer.

AI Research Engineer, Data InfrastructureLocation: Palo Alto, CA (on-site)About 1XAt 1X, we are at the forefront of innovation, developing humanoid robots designed to collaborate with humans, effectively addressing labor shortages while fostering abundance across industries.The RoleAs an AI Research Engineer specializing in Data Infrastructure, you will play a pivotal role in designing and implementing a comprehensive data engine to efficiently manage the vast data generated by our humanoid robot fleet. Your contributions will ensure that this data is readily accessible for querying and training, supporting the development of high-quality data pipelines that facilitate effective model training, large-scale data annotation, and seamless integration across robotic, on-premise, and cloud-based systems.

About VoltaiAt Voltai, we are pioneering the development of world models and agents capable of learning, evaluating, planning, experimenting, and interacting with the physical realm. Our journey begins with a focus on hardware, specifically in electronics systems and semiconductors, where we harness AI to design and innovate beyond human cognitive capabilities.About the TeamOur team boasts extraordinary talent, including esteemed former Stanford professors, SAIL researchers, and medalists from prestigious competitions like IPhO and IOI. We are supported by top-tier investors from Silicon Valley and industry leaders, including CEOs and Presidents from Google, AMD, Broadcom, and Marvell.About the RoleAs a Research Engineer specializing in CUDA Kernel engineering, you will design, integrate, and optimize cutting-edge CUDA kernels that drive AI models, facilitating rapid advancements in semiconductor design and verification. Your contributions will empower extensive model training, inference, and reinforcement learning systems capable of reasoning about circuit layouts, generating and validating RTL, and optimizing chip architectures, all while efficiently utilizing thousands of GPUs.You will create tools, performance benchmarks, and integration layers that maximize GPU utilization for compute-intensive workloads in AI-driven hardware design. Collaborating closely with fellow researchers and engineers, you will help position Voltai as the foremost organization in AI and semiconductor research. Furthermore, your kernels and tools will be released as valuable contributions to the open-source AI and HPC ecosystems.You might excel in this position if you possess experience in:Writing and optimizing CUDA kernels for large-scale AI applications (e.g., attention mechanisms, routing, graph-based operations, and physics-inspired operators).Profiling and enhancing GPU performance for specialized compute or memory-bound workloads.Integrating custom kernels into state-of-the-art training and inference frameworks (including PyTorch, Megatron, vLLM, and TorchTitan).Engaging with the latest NVIDIA hardware and software frameworks (Hopper, Blackwell, NVLink, NCCL, Triton).Creating GPU-accelerated primitives for graph reasoning, symbolic computation, or hardware simulation tasks.

Join Our TeamAt Parallel, we are at the forefront of web infrastructure innovation, empowering businesses in various sectors—sales, marketing, insurance, and technology—to develop sophisticated AI agents equipped with robust programmatic access to the internet.Having secured $130 million in funding from prestigious investors such as Kleiner Perkins, Index Ventures, Spark Capital, Khosla Ventures, First Round, and Terrain, we are building a premier team of engineers, designers, marketers, sales professionals, researchers, and operational specialists to fulfill our ambitious vision.Your ProfileWe are looking for a researcher who embodies an engineering mindset, or an engineer who approaches problems with curiosity typical of researchers. You may have experience with information retrieval systems, embedding models, or neural ranking at scale, or possess a deep interest in the challenges of training models to comprehend and navigate billions of web pages. You will excel in the intersection of theory and practical application, devising elegant solutions that perform efficiently on real-world infrastructure. You'll be equally comfortable reading the latest papers from SIGIR and RecSys as you are troubleshooting distributed training pipelines.Position OverviewIn this role, you will design and train models that drive Parallel's APIs—the intelligent framework that enables AI agents to extract precise information from the open web. This involves addressing complex research challenges that most labs only encounter at scale: How can we create embedding models that accurately represent semantic intent across various query types? How do we achieve a balance between model expressiveness and sub-second retrieval times? How can we ensure our index remains up-to-date with the constantly evolving web, without the need for complete rebuilds?Unlike conventional search engines tailored for human queries, you will be developing solutions for AI agents that generate intricate, multi-hop queries, requiring structured, programmatic responses. This is information retrieval redefined for the era of large language models, merging traditional information retrieval methods with cutting-edge deep learning, applied at a scale that necessitates innovative solutions.Working EnvironmentOur team collaborates fully in-person at our headquarters in Palo Alto and our San Francisco office. We pride ourselves on being a flat, talent-rich organization committed to tackling both technical and creative challenges.We are eager to welcome individuals who share our enthusiasm for leveraging science, creativity, and consistency to address large, complex problems with significant impacts. Here are our core values:Customer Impact Ownership: We take responsibility for delivering tangible results for our clients.

About VoltaiAt Voltai, we are pioneering advancements in artificial intelligence by developing sophisticated world models and agents that learn, evaluate, plan, and interact with the physical environment. Our primary focus lies in enhancing hardware capabilities, particularly in electronics systems and semiconductors, where AI can surpass traditional human cognitive limitations in design and creation.About the TeamOur team comprises exceptional talent, including former Stanford professors, acclaimed SAIL researchers, Olympiad medalists, and industry leaders from renowned companies such as Google, AMD, and Broadcom. We are supported by top investors from Silicon Valley and have a diverse group of experts, including former U.S. government officials, committed to driving innovation in AI and hardware design.Role OverviewAs a Post-Training Research Engineer, you will focus on post-training cutting-edge models to autonomously execute intricate tasks within the semiconductor design and verification pipeline. The models you help develop will optimize chip architectures, refine RTL code, conduct simulations, identify verification gaps, and iteratively enhance designs to expedite semiconductor innovation. You will work alongside leading experts in hardware design and verification, crafting comprehensive reinforcement learning environments that encapsulate the complexities of chip design workflows. Your contributions will involve developing structured reward functions, scaling strategies, and evaluation frameworks aimed at enhancing model reliability, efficiency, and creativity in semiconductor reasoning.Ideal Candidate ProfileYou may excel in this role if you possess experience in:Creating and scaling reinforcement learning environments for large language models or multimodal agents.Building high-quality evaluation datasets and benchmarks for complex reasoning or design challenges.Collaborating closely with domain experts in hardware and verification to establish evaluation metrics, constraints, and simulation conditions.Designing reward functions and feedback pipelines that ensure a balance between correctness, performance, and design efficiency.Conducting large-scale reinforcement learning fine-tuning or post-training experiments on frontier models.