Research Chemist Jobs

About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $22B - multiples of 11, always. We have expanded from voice into three main platforms: ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. How we work High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. Excellence everywhere: Everything we do should match the quality of our AI models. Global team: We prioritize your talent, not your location. What we offer Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. Growth paths: Joining ElevenLabs means joining a

Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities. In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models. You will: Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA. Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities. Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development. Excellent written and verbal communication skills. Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals. Previous experience in a customer facing r

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. Join NVIDIA's Nemotron Harness team. We are leaders in AI research, exploring machine learning, reinforcement learning, computer vision and natural language processing. As a Research Scientist, you will work on projects that seek to redefine general intelligence. This Zürich, Switzerland position offers an outstanding platform to participate in innovative research and impact the future of AI. What you will be doing: Conduct groundbreaking research to advance the science and technology of intelligent machines. Co-develop models with harnesses, increasing task horizon, improving memory and general intelligence capabilities in VLM/LLM systems. Work towards daring long-term research goals, while identifying and achieving immediate achievements. Influence the research community through high-quality publications and collaborative efforts. Open source high-quality code and ensure the reproducibility of your research. What we need to see: PhD or equivalent 6+ years of experience in Computer Science, relevant technical field, or similar, completed prior to joining NVIDIA. Research background in machine l

At Dscout, we’re building the most flexible and powerful UX research platform on the market—trusted by the world’s top brands in finance (JP Morgan Chase, Intuit, Charles Schwab, PayPal), healthcare (Aya, Headspace), consumer goods (Keen, Verizon, Target, Northface), and tech (Google, Amazon, Facebook, Meta, Spotify, AirBnB). Our tools help teams deeply understand the humans behind their products, so they can build better ones. We are expanding our smart and driven team and would love for you to join us. We are looking for a Research Advisor to join our growing Customer Experience and Research (CXR) team. In this position, you will work collaboratively with Lead Research Advisors and Dscout clients to help our customers use our platform to design, recruit and field research projects. Our clients conduct research on a wide range of topics varying across: technology, retail, healthcare, and AI, just to name a few. You will have a chance to make a real difference for Dscout’s customers and build your career in the worlds of research and customer success. You are an incredible communicator and a genuine, creative problem-solver. You’re the client’s partner in learning a new digital tool to execute powerful research. You collaborate with clients as they develop research plans, and help to identify Dscout methodologies that best meet their needs. Internally, you are our clients’ champion to drive larger improvements to the platform and overall user experience. The Research Advisor position is among the most central to Dscout’s operations, and means you’ll work with people from across the company on a regular basis, especially our product, engineering and sales teams. If this sounds exciting to you, apply today! What you will do: Act as a true Dscout expert to train and educate clients on features and functionalities Provide specific recommendations for clients’ research design on Dscout Assist in running clients’ research projects on Dscout in

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. About the Role, Mission or Department Overview The Research Director, Content Insights will have a critical role informing the creation, iteration and measurement of video and video products at the New York Times. You will lead all video measurement research to inform our understanding of how video content performs across platforms, surfaces, and audience segments. You will oversee the end-to-end measurement of video effectiveness, from individual videos to longer-form recurring concepts, and translate data into relevant strategies that inform production, distribution, and editorial decisions. You will also work with product, design, and editorial teams to improve on-platform video experiences. You will report to the Managing Director, News Products on the Audience Insights Team and will collaborate with partners across the Newsroom. You understand how to blend market research and user research methods and practices into actionable insights for an entire mission. This is a hybrid role based in our New York City headquarters. You can typically expect to come into the office 3 days per week. Responsibilities: Develop audience research to support the creation and growth of video franchises and recurring shows. Drawing on research methods used by production studios and streaming networks, you'll conduct research that can inform greenlight decisions — including concept testing, pilot testing, audience appetite studies, and competitive landscape a

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role As an Applied Research Engineer in our Video team, you will help build the next generation of production-grade foundation models for human-centric video generation. You will join a highly focused team working at the intersection of large-scale generative modeling, distributed systems, and production engineering. Our mission is to develop and optimize video base models that power realistic, controllable, and emotionally expressive synthetic humans at scale. This is not pure research. This is applied research with direct product impact. You will work on advancing training recipes, scaling distributed systems, improving evaluation frameworks, and optimizing inference to ensure our models are high quality, stable, and efficient enough for real-world deployment. Your work will directly influence models used by tens of thousands of businesses worldwide. What you’ll do You will own and execute end-to-end research and engineering projects, from hypothesis to production impact. This includes: Developing and scaling latent video diffusion models tailored for human-centric video generation Designing conditioning mechanisms to improve control (pose, emotion, script, camera) without sacrificing fidelity Advanc

About the Team The Health team, within OpenAI’s broader Personal AGI organization, has a mission to ensure AGI improves health for all humanity. Improving human health will be one of the defining impacts of AGI. Hundreds of millions of people already turn to ChatGPT for questions about their health and millions of clinicians use it weekly to support care delivery. Increasingly capable models create an opportunity to make high-quality medical intelligence more accessible across patients and clinicians—raising the floor of human health—and accelerate the new capabilities and scientific advances that raise the ceiling of human health. Our job is to make those benefits real. We work across the full model stack—pretraining, midtraining, reinforcement learning, post-training, evaluations, harnessing, and deployment—and connect that research to the patients, clinicians, and real-world outcomes we aim to improve. About the Role We’re looking for an exceptional, hands-on researcher who wants to build frontier health capabilities and turn them into impact at scale. This is a role for someone who can take an important, underdefined problem from 0→1: identify the right bet, build what’s needed to test it, and drive it all the way to a measurable improvement in the models and products we actually ship. We’re especially excited about two kinds of people: researchers with the technical depth to move the frontier in pretraining, reinforcement learning (RL) / post-training, or evals; and researchers with real depth in developing frontier biomedical AI capabilities. Prior experience in healthcare is helpful but not required. Research excellence, velocity, ownership, and alignment with the mission are most important to us. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own a high-leverage research direction end to end—from deciding which problem matters and h

The Performance Research Engineer will play a critical role in advancing TaylorMade's leadership in golf equipment performance. This role bridges physical testing, player testing, Tour-level data collection, and advanced analytics to deliver actionable insights that influence product design, product validation, and performance optimization. The ideal candidate is a hands-on engineer with strong mechanical aptitude, advanced data skills, deep golf intuition, and the ability to translate player feedback into clear engineering direction. Essential Functions and Key Responsibilities: Lead the design and execution of advanced performance testing protocols for golf clubs and balls, including lab, player, field, and Tour-based testing environments. Serve as a category-focused Performance Engineering owner for one or more product areas, with potential emphasis across Woods, Irons, Putter/Wedge, or cross-category initiatives. Support PGA/LPGA Tour and elite-athlete testing by collecting clean, repeatable, decision-ready data while operating professionally and respectfully in player-facing environments. Analyze large datasets from lab, player, and field testing to extract insights on ball speed, launch, spin, consistency, delivery, impact location, dispersion, and performance tradeoffs. Translate Tour and player-test observations into clear engineering recommendations, product questions, validation plans, and follow-up experiments. Develop and maintain automated data pipelines, dashboards, and reporting tools for performance tracking, project communication, and cross-functional decision-making. Collaborate with R&D, Product Development, Tour, Fitting, Consumer Insights, and Analytics teams to integrate player feedback and real-world data into product design.

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? To have the opportunity to collaborate with Cohere researchers and tools on designing and implementing novel research ideas and shipping state-of-the-art models to production. We have openings in teams covering base model training, retrieval augmented generation, data and evaluation, safety, and finetuning, to name a few; and we are open to receiving intern applications in any research area relating to LLMs to broaden your research connections while obtaining deep experience in a growing AI startup. Please Note: To be eligible for a Research Internship, you must be currently pursuing a PhD in Machine Learning, NLP, or a related discipline. You need to be available for a full-time internship that lasts for 4-6 months. As a Cohere Research Intern, you will: Conduct cutting-edge machine learning research, building and training large language models. Focus on research projects aimed at expanding the frontier of knowledge in language modelling and associate areas such as evaluation, multimodal models, optimisation etc. Disseminate your research results through the production of publications, datasets, and code. Contrib

About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Team: The LangSmith Engine team is building a proactive agent engineer that analyzes production traces, identifies important failures, recommends and writes fixes, and helps prevent those issues from coming back. We’re building agents that can understand complex software systems and continuously improve the quality of other AI agents. About the Role: We’re looking for an experienced research engineer to help make the Engine agent more capable and more efficient. You’ll study real agent failures, build benchmarks that capture what matters, run experiments to improve performance, and turn successful ideas into production. This may include prompting and agent-harness i

Overview: The Insights product is a new offering for Guidepoint's Institutional investment and corporate clients, that offers teleconferences, surveys, and in-person events. The teleconferences live in a transcript library portal, which covers a wide of industries/topics that enables our clients to make informed decisions. All content features experts from Guidepoint’s proprietary global network and is conceptualized and hosted by former investment professionals (i.e., private equity/hedge fund), sell-side equity research analysts, and industry professionals. Visit Insights team biographies at https://www.guidepoint.com/insights/#team . What You’ll Do: Work closely with the Insights team to execute teleconferences that will cover a wide range of sectors including tech/media/telecom, consumer, industrials/materials/energy, healthcare and financials Proactively monitor pipeline of upcoming call topics so experts can be identified or selected 1-2 weeks before scheduled call date Utilize the phone, LinkedIn, and outreach to recruit new Advisors to join the Guidepoint network and communicate with potential experts to answer questions or discuss/verify their credentials Recruit new advisors to join the Guidepoint network, using a variety of outreach tools and resources provided. Communicate with potential experts via phone to answer questions or discuss/verify their credentials Develop effective screening criteria for experts to test knowledge of subject matter; Review responses to screening questions from experts to gauge sufficient knowledge of subject matter Finalize scheduling and call logistics details directly with experts What You Have: Bachelor’s degree or higher with strong academic record is required 1-2 years of work experience in pre-sales/ sales/ client service/ customer support/ BPO/ lead generation Prior experience in cold calling and sending cold emails, generating leads would be great Excellent communication and interaction skills, including demonstrated

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team The Biohub is a group of nonprofit research institutes that bring together scientists, engineers, and physicians with the goal of pursuing grand scientific challenges on 10- to 15-year time horizons. The Biohub focuses on understanding underlying mechanisms of disease and developing new technologies that will lead to actionable diagnostics and effective therapies. Our Vision We pursue large scientific challenges that cannot be pursued in conventional environments We enable individual investigators to pursue their riskiest and most innovative ideas The technologies developed at the Biohub facilitate research by scientists and clinicians at our home institutions and beyond Diversity of thought, ideas, and perspectives are at the heart of Biohub and enable disruptive innovation and scholarly excellence. We are committed to cultivating an organization where all colleagues feel inspired and know their work makes an important contribution. This role sits at the interface of two closely connected efforts within our Dynamic Structural Biology group, which maps the molecular architecture of living cells — charting how protein complexes assemble, where they localize, and how their organization shifts across cell states and in response to perturbation. We develop and operate advanced imaging workflows to resolve the structure of signaling organelles such as primary cilia and lysosomes. Together we develop and deploy cutting-edge cryo-electron tomography, proteomics, and correlative imaging ap

About Appier Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. About the Role As a Research Scientist, you will work at the frontier of generative and agentic AI: advancing Large Language Models (LLMs) , Vision-Language Models (VLMs) , and AI agents that reason, plan, and use tools to solve real-world problems. Your research will span post-training (SFT, RLHF/RLVR), reasoning and test-time scaling, multimodal intelligence, and autonomous agentic systems. You will shape Appier's core AI capabilities, publish at top AI/ML conferences, and collaborate with scientists and engineers to turn frontier research into product impact. Responsibilities Research and build agentic AI systems : reasoning, planning, tool use, memory, and multi-agent collaboration, powered by LLMs and VLMs. Advance post-training techniques (SFT, RLHF, RL with verifiable rewards, preference optimization) to improve model capability, alignment, and reliability. Improve the performance, efficiency, and scalability of foundation models across training, inference, and test-time compute. Design rigorous evaluations and benchmarks for models and agents in real-world scenarios. Collaborate with cross-functional teams to ship research into production applications. Track frontier research, propose new directions, and publish key findings at leading AI/ML venues. About You Minimum Qualifications Master's degree or Ph.D. in Computer Science, Electrical Engineering, Mathematics, or a related field, with research experience in AI/ML. Deep understanding of modern foundation models, with expertise in at least one of: LLMs, VLMs/multimoda

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. Research Analyst (X Corp.; New York, NY): Produce financial and market intelligence by querying data repositories and generating periodic reports. Formulate and apply mathematical modeling and other optimizing methods to develop and interpret information that assists management with decision making, policy formulation, or other managerial functions. Analyze the company’s position in the industry and develop relevant strategies to drive revenue. Pull and analyze data to determine the company’s position within the industry while conducting Ad-hoc Client Analyses. Drive clients’ key performance metrics and return on their ad investment through optimization of ad campaigns. Participate in weekly Data Science Center of Action meetings, the purpose of which is consulting on ongoing projects within other teams and knowledge sharing among MI and A analysts. Responsible for providing customized measurement products to key clients. Research products commissioned to external vendors. Represent the company at internal and external events while maintaining significant business relationships with key clients and partners. Telecommuting within the US permitted pursuant to company policy. Refer

About the Team The Recursive Self-Improvement (RSI) team works across research, engineering, product, and infrastructure to build AI systems that accelerate and ultimately conduct high-quality research at OpenAI. We work to automate real research workflows and improve research productivity by building systems and feedback loops, designing evaluations, and training models to develop missing capabilities. Our work spans the full lifecycle of model training, evaluation, and deployment to help researchers move faster and tackle increasingly ambitious problems. About the Role We’re hiring research scientists , research engineers , and AI systems engineers to work on automating research at OpenAI. This role is based in San Francisco, CA. In this role, you will: Design evaluations for research judgment, hypothesis generation and testing, and long-horizon experiment execution. Turn real research workflows and model failures into data and evaluation flywheels. Improve model research capabilities through agent harnesses, synthetic data, RL environments, and model training. Build and maintain safe, reliable integrations between our models and OpenAI’s research infrastructure. Develop research agents, experiment-orchestration systems, and sandboxed runtimes that support real research workflows. Create metrics and economic models to understand RSI’s current and future effects on research productivity, model capabilities, and the safety of internal deployments. This is a high-ownership role for researchers and engineers who thrive in ambiguity, move fluidly between research and implementation, and turn emerging opportunities into rigorous, reliable, scalable results. You might thrive in this role if you: Have research or engineering experience across LLM training, model evaluations, agent systems, synthetic data, research infrastructure, or large-scale distributed systems. Are a strong generalist who can move between open-ended research and practical implementation, turning ambig