Machine Learning Research Scientist - Interpretability

Become part of an innovative team that is pioneering the development of the world's first biological reasoning model. Collaborate with us to create generative foundational models that unravel biological systems on various scales—from molecules to entire organisms—empowering us to predict, comprehend, and manipulate living systems in unprecedented ways.Output Biosciences is currently operating in stealth mode, led by a team of experienced founders and biotech experts with a proven track record in AI and biology, supported by top-tier venture capital firms including Y Combinator.As a Machine Learning Research Scientist specializing in Interpretability, you will collaborate closely with our founders and dedicated team to create AI systems that can process and reason across diverse biological data modalities simultaneously.Develop specialized techniques to enhance the understanding of our biological reasoning models, reverse-engineering their representation and processing of complex biological information.Design and perform experiments aimed at discovering interpretable features across various biological scales.Tackle unique challenges in biological model interpretation, including disentangling multi-scale, hierarchical representations of biological systems.Create biology-specific visualization tools that effectively map model activations to meaningful biological concepts.

About BasisBasis is a pioneering nonprofit organization dedicated to applied AI research. Our mission is twofold: to deepen our understanding of intelligence and to empower society in solving complex, challenging problems.Our first objective is to comprehend and construct intelligence. This involves establishing foundational mathematical principles for reasoning, learning, decision-making, comprehension, and explanation, while also developing software that embodies these principles.Secondly, we aim to enhance society’s capability to tackle intractable issues. This includes broadening the scope and complexity of problems we can address today and accelerating our future problem-solving abilities.To accomplish these objectives, we are creating a technological infrastructure inspired by human reasoning and fostering a collaborative organization that prioritizes human values.About the RoleAs a Research Scientist, you will spearhead Basis’ initiatives to unravel the conceptual, mathematical, and computational foundations of intelligence. We seek individuals with exceptional technical skills who are eager to explore foundational concepts. Our research scientists and engineers are committed to conducting rigorous, high-quality scientific investigations, while also embracing the opportunity to experiment, learn from errors, and explore innovative ideas.Collaboration is integral to our work, both internally and with external partners. We are searching for individuals who thrive in team settings, tackling challenges that transcend individual capabilities.Key Expectations:Proven ability to conduct high-quality scientific research, demonstrated through publications, technical reports, or software projects.Preferred Qualifications:PhD or equivalent experience in relevant fields such as statistics, programming languages, machine learning, computational neuroscience, cognitive science, physics, or mathematics.Enthusiasm for addressing real-world challenges and contributing to positive societal change.ResponsibilitiesDevelop and investigate computational theories of intelligence, encompassing reasoning, learning, and decision-making.Collaborate closely with domain experts, both within Basis and externally, to contribute to solving scientific problems.

Become a pivotal part of our innovative team at Output Biosciences, where you will contribute to the groundbreaking development of the world's inaugural biological reasoning model. Collaborate with us in creating generative foundational models that decode biological systems at all scales—from molecules to entire organisms—allowing us to predict, understand, and manipulate living systems in unprecedented ways.Currently operating under stealth mode, Output Biosciences is spearheaded by a team of accomplished founders and seasoned biotech veterans with a proven track record of successful exits in both AI and biology. We are proudly backed by leading venture capital firms including Y Combinator.As a Machine Learning Research Scientist specializing in Generative AI, you will work closely with our founders and collaborative team members to forge advanced generative models capable of synthesizing and designing biological systems across various scales. Building on our biological reasoning model, your focus will be on creating generative capabilities that translate insights into innovative applications.Design and develop state-of-the-art generative models tailored for biological data, enabling AI systems to generate novel molecular structures, protein designs, cellular components, and biological pathways.Implement cutting-edge generative algorithms including diffusion models, language diffusion models, diffusion transformers, and flow matching approaches, customized for biological constraints and properties.Train and scale pioneering AI models utilizing large, diverse multimodal biological datasets across distributed GPU clusters.Solve complex AI research challenges at scale, addressing crucial aspects like model architecture, scaling, pre-training and fine-tuning strategies, and rigorous evaluation methods.Explore and implement various advanced generative AI architectures, such as transformers, diffusion models, and autoencoders, to push the boundaries of biological AI innovation.

About BasisBasis is a nonprofit organization dedicated to applied AI research, striving to achieve two interconnected objectives.Firstly, we aim to understand and develop intelligence. This involves establishing the mathematical foundations of reasoning, learning, decision-making, comprehension, and explanation; along with creating software that embodies these principles.Secondly, we seek to enhance society's capacity to address complex challenges. This means broadening the range, scale, and intricacies of the problems we can tackle today, while also accelerating our ability to solve future challenges.To fulfill these missions, we are constructing a novel technological framework inspired by human reasoning, and fostering a collaborative organization that prioritizes human values.About the RoleAs a Research Scientist, you will spearhead Basis's initiatives to deepen our comprehension of the theoretical, mathematical, and computational aspects of intelligence.We seek individuals with exceptional technical skills who are passionate about exploring concepts at their core. Our research scientists and engineers are committed to conducting rigorous, high-quality, and robust scientific inquiry, yet they embrace experimentation, learning from mistakes, and exploring innovative ideas to achieve their goals.Basis thrives on collaboration, both internally and with external partners; thus, we value team players who relish tackling challenges that surpass individual capabilities.Research FocusOur research under the MARA project is dedicated to forging new principles and technologies for modeling, abstraction, and reasoning in AI systems. The primary aim of MARA is to reveal principled methodologies for how intelligence constructs, refines, and applies world models through interactive experimentation.For this position, we specifically seek experts in Reinforcement Learning & Planning who can push the boundaries of model-based RL, exploration strategies, optimal control, and Bayesian optimization. You will develop agents capable of learning efficient policies in intricate, partially observable environments by utilizing structured world models.

About BasisBasis is a pioneering nonprofit organization dedicated to applied AI research, driven by dual objectives that enhance each other.Our primary focus is to understand and construct intelligence. This encompasses establishing the fundamental mathematical principles of reasoning, learning, decision-making, comprehension, and explanation, alongside developing software that embodies these principles.Secondly, we aim to empower society to tackle complex challenges. This involves broadening the scale, complexity, and scope of problems we can currently address and, crucially, accelerating our future problem-solving capabilities.To realize these ambitions, we are establishing an innovative technological framework inspired by human reasoning and fostering a collaborative environment that prioritizes human values.About the RoleAs a Research Engineer, you will play a vital role in advancing Basis’ mission by converting research concepts into accurate, robust, and scalable high-quality code.We are looking for technically proficient individuals who are enthusiastic about delving deep into foundational concepts. Our research engineers are committed to conducting rigorous, high-quality science, unafraid to experiment, learn from mistakes, and explore innovative ideas.Basis thrives on collaboration, both within our team and with external partners. We seek individuals who enjoy tackling challenges greater than they can manage alone.Machine Learning Research Engineer Focus AreasThis position is aimed at experts in machine learning engineering. Key areas of focus include:Probabilistic programming and statistical inferenceDeep learningCausal inferenceProgram synthesis and analysisML Ops and systems engineeringThese areas will be explored in the context of developing reasoning systems. Research engineers will also engage with topics including programming language design and implementation, automatic differentiation, and SAT/SMT solvers.

Join The New York Times as a Machine Learning Scientist, where you will leverage advanced machine learning techniques to enhance user engagement and content discovery across our digital platforms. Collaborate with a talented team of data scientists and analysts dedicated to revolutionizing the way our audience interacts with journalism. Your role will involve translating business objectives into actionable machine learning tasks, developing innovative algorithms, and ensuring the deployment of robust models with a focus on reproducibility and ethical considerations.

Who We AreAt Percepta, our mission is to revolutionize essential sectors through applied AI. We are dedicated to ensuring that key industries, such as healthcare, manufacturing, and energy, leverage cutting-edge technology. By collaborating with industry leaders, we facilitate AI transformation.Expertise in engineering, product development, and research.Mosaic, our proprietary toolkit for swift deployment of agentic workflows.Strategic alliances with companies such as Anthropic, McKinsey, AWS, and others in the General Catalyst portfolio.Our team is rapidly expanding, consisting of Applied AI Engineers, Embedded Product Managers, and Researchers who are passionate about integrating AI advancements into our daily lives. Percepta is a direct partnership with General Catalyst, a global leader in transformation and investment.About the RoleAs a Research Engineer/Scientist (Optimization) at Percepta, you will play a crucial role at the convergence of AI research and impactful real-world applications. You will push the boundaries of decision-making in vital industries by integrating state-of-the-art machine learning with robust optimization research. Collaborate closely with our Embedded Product Managers (EPMs) and engineers to ensure that our advanced decision systems are both innovative and practically beneficial for transforming organizational operations.ResponsibilitiesEstablish and lead ambitious research initiatives that broaden the horizons of data-driven decision-making.Develop innovative optimization and machine learning methodologies for significant challenges such as planning, scheduling, routing, pricing, and inventory management.Create high-fidelity simulators and comprehensive benchmarks that accurately reflect real-world constraints, uncertainties, and multi-objective trade-offs.Translate research into practical applications by partnering with engineers to swiftly prototype solutions and effectively implement research insights.You May Be a Great Fit If YouHold a degree in Computer Science, Operations Research, Industrial Engineering, or Applied Mathematics (MS/PhD preferred) or possess equivalent research or industry experience.Have demonstrated experience in optimization and machine learning.Exhibit a strong ability to collaborate and communicate effectively across multidisciplinary teams.

Jump Trading Group is at the forefront of world-class research, empowering talented individuals in Mathematics, Physics, and Computer Science to explore scientific boundaries and apply innovative research to the global financial markets. Our unique culture thrives on constant innovation, which requires creativity, intellectual honesty, and a relentless competitive spirit. We believe in collaborative success, unlocking individual talents through mutual respect and teamwork. At Jump, our research not only drives superior risk-adjusted returns but also leads to the development of transformative technologies that impact the world, funding startups across various industries, and partnering with premier research organizations and universities to tackle complex challenges.Our AI team serves as a pivotal research and development hub, consisting of quantitative researchers, engineers, and machine learning experts dedicated to advancing large language model (LLM) research and its applications. Our mission is to merge cutting-edge techniques with original research to derive actionable insights from unstructured data.

About Mirage Mirage builds an AI-powered video platform that brings production and editing together through natural language. The team focuses on models with strong contextual understanding, aiming to match the creative decisions of skilled editors. This approach boosts productivity for experienced teams and makes advanced video creation accessible to a wider audience. Learn More Product: Captions by Mirage Research: Seeing Voices (technical white paper) Updates: Mirage on X / Twitter Press: TechCrunch, Forbes AI 50, Fast Company Investors Mirage is backed by leading investors and entrepreneurs, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, and General Catalyst. Role Overview: Research Scientist, Video Generation This position is based at Mirage’s headquarters in Union Square, New York City. In-person attendance is required. Mirage seeks a Research Scientist with a focus on video generation. As an early member of the team, this person will help address foundational challenges in generative media. The role involves developing new modeling techniques, designing training methods, and scaling large video models for real-world use. Work in this area shapes systems used by millions of creators. What You Will Do Advance the quality, controllability, and realism of video generation models Focus on areas such as facial expression synthesis and scene understanding Develop and refine modeling and training strategies for large-scale video systems Collaborate with an interdisciplinary team to solve technical and creative challenges in generative media

About BasisBasis is a pioneering nonprofit organization dedicated to applied AI research, driven by two key objectives.The first objective is to comprehend and develop intelligence. This encompasses establishing the mathematical foundations of reasoning, learning, decision-making, understanding, and explanation, while also creating software that embodies these principles.The second objective is to enhance society’s capacity to tackle complex challenges. This involves broadening the scope, scale, and complexity of problems we can address today, and crucially, accelerating our capacity to solve future problems.To fulfill these missions, we are constructing an innovative technological infrastructure inspired by human reasoning, along with a collaborative organization that prioritizes human values.About the RoleAs an ML Systems Engineer at Basis, you will ensure that our training and evaluation infrastructure is fast, reliable, and scalable. You will manage the entire stack, from distributed training frameworks to cloud administration, enabling researchers to rapidly iterate on complex models while efficiently managing computational resources.We are seeking engineers who possess a profound understanding of ML systems paired with operational excellence. The ideal candidate will have experience in distributed training at scale, expertise in debugging numerical instabilities, and the ability to manage cloud infrastructure that seamlessly transitions from experimentation to production. You will be the steward of training stability, an optimizer of computational costs, and a facilitator of reproducible research.This position encompasses both traditional ML engineering and cloud/DevOps responsibilities. You will oversee GPU clusters, optimize cloud expenditures, ensure security and compliance, and build the infrastructure that allows researchers to focus on algorithms rather than operations.We are looking for individuals who are committed to developing robust ML infrastructure, maintaining a culture of documentation for issues and solutions, and prioritizing operational excellence as a core value.

OverviewAt OXMAN, a pioneering nature-focused research and design firm based in Manhattan, we leverage nature-centric solutions to tackle pressing challenges at the intersection of Nature and Humanity. Our interdisciplinary approach spans various sectors, fostering innovative concepts that redefine the interaction between the built environment and the natural ecosystem.Our initiative, EDEN, is dedicated to applied ecological systems operating on architectural, urban, and landscape scales. We are at the forefront of creating a digital design framework that engineers biodiverse and resilient ecosystems by developing software that empowers designers and engineers to incorporate essential ecosystem services—such as carbon sequestration, thermal buffering, and biodiversity—into their master planning and design processes. Our mission is to elevate ecosystem services from undervalued byproducts to vital infrastructure elements. We invite talented professionals to join us in revolutionizing the future of nature-centric design.We are currently seeking a Machine Learning Research Engineer to integrate into our dynamic design team in New York City. This role will be pivotal in supporting our efforts to deliver exceptional, data-driven design proposals utilizing EDEN’s innovative suite of ecosystem engineering tools.

About the Role Robinhood Markets, Inc. is hiring a Senior Data Scientist focused on Machine Learning for the Brokerage team. This role is based in Menlo Park, CA or New York, NY. What You Will Do Apply advanced data analysis and machine learning techniques to strengthen the trading platform. Work closely with colleagues across product, engineering, and operations to develop data-driven tools and features. Identify patterns and generate insights that support a better user experience and greater operational efficiency. Collaboration This position partners with cross-functional teams to design and implement solutions that address real needs within the Brokerage division.

Join our innovative AI Research team at Datadog as an AI Research Scientist. Collaborate with talented research engineers and work closely with our Product and Engineering teams to transform cutting-edge research into valuable solutions for our customers.At Datadog AI Research, we are proud of our successful AI-driven solutions, including Bits AI, Watchdog, and Toto. Our focus is on tackling high-stakes, ambitious projects that address real-world challenges in cloud observability and security.We are currently concentrating on three pivotal research areas:Observability Foundation Models – Developing advanced models for forecasting, anomaly detection, and comprehensive telemetry analysis across logs, metrics, and traces. These models will empower our agents to analyze telemetry data effectively.

Hello! I'm Brian, Co-Founder of Egra. We are thrilled to announce that we have successfully raised $5.5 million to develop foundational models for interpreting brain signals, and we are eager to welcome our inaugural research scientist to our innovative team.In this role, you will be empowered to take complete ownership of your projects from the outset. Say goodbye to prolonged onboarding processes, the need for excessive approvals, and bureaucratic hurdles. You will collaborate directly with the founders, tackling complex technical challenges and utilizing the resources available to drive solutions. You will have the unique opportunity to shape the research vision, make key architectural choices, and lay the groundwork for our core technology. If you're someone who thrives in an environment that offers high autonomy and desires to make a significant impact on the direction of a pioneering company, this role is perfect for you.Key ResponsibilitiesEEG (electroencephalography) is one of the most challenging real-world signal modalities in machine learning due to its low signal-to-noise ratio, vast subject variability, and inconsistencies across devices. Many shy away from this domain for these reasons.As our founding research scientist, you will collaborate closely with us to discover effective methodologies. Here’s a glimpse into the projects you will spearhead:Developing self-supervised pretraining objectives that enhance generalization across various subjects, devices, and recording conditions.Critically evaluating existing methods (including recent EEG foundation model studies) to identify their limitations across datasets and conditions, particularly under distribution shifts.Creating robust evaluation protocols that effectively differentiate genuine progress from noise, ensuring we maintain rigorous benchmarks.Documenting internal research findings through comprehensive memos that contribute to the lab's collective knowledge — addressing questions like "why model X fails on dataset Y" and "what Z dataset misleads us about".This position is about cultivating a thorough understanding of a modality that remains largely unexplored with modern machine learning approaches and transforming this insight into impactful advancements.Vision for the FutureWe are striving towards a future where thought serves as a direct interface.Imagine composing a message silently as it types itself or navigating an AR environment without any physical interaction. Software that adapts to your cognitive state in real-time. We are developing a universal interface connecting human cognition with digital actions.Our product development encompasses three pivotal layers:A Neural Encoder: a foundational model designed to translate raw EEG data into resilient, reusable embeddings that function seamlessly across diverse devices and recording environments.

Join Duolingo, the world's leading language-learning platform, as the Principal Learning Scientist and Head of Efficacy Research. In this pivotal role, you will spearhead innovative research initiatives to assess and enhance the efficacy of our educational products. Your expertise will guide the development of evidence-based strategies that ensure our learners achieve their language goals effectively.As the Head of Efficacy Research, you will collaborate with cross-functional teams, including product development and data analytics, to design robust research methodologies. You will analyze user data and feedback, translating insights into actionable recommendations that drive product improvements. This is an exciting opportunity to influence the future of language education on a global scale.

Hello! I’m Aidan, the founder of Maple.At Maple, we are on a mission to revolutionize local businesses by creating intelligent AI agents. Our agents efficiently manage tasks such as answering calls, taking orders, and booking appointments, providing seamless interactions through natural voice communication.Our deeper mission: We are developing automated ontologies that accurately reflect the operational realities of businesses — capturing their services, workflows, constraints, and unique language — allowing our agents to adapt instantly to diverse business needs. We strive to meet businesses where they are, rather than imposing a rigid software framework.With a growing customer base, strong revenue growth, a secure financial runway, and support from esteemed investors, we are positioned for exciting advancements. More details will be shared during our conversation.Role OverviewAs a Machine Learning Research Engineer at Maple, you will be integral to our core product team, transforming innovative research into production-ready voice agents that facilitate millions of customer interactions for small businesses. You will collaborate with experts from prestigious institutions such as Google Brain, Two Sigma, Stanford, MIT, Columbia, and IBM to swiftly deploy sophisticated models and systems that have a direct impact on small enterprises.Our team operates in person, five days a week in our vibrant NYC office. Our collaborative environment is characterized by rapid-paced, dynamic interactions filled with trust and transparency. We embrace a culture of speed and adaptability, tackling challenges head-on.Key ResponsibilitiesEnhance automatic speech recognition (ASR), large language models (LLMs), and text-to-speech (TTS) systems for practical applications, ensuring high accuracy in diverse and noisy environments.Fine-tune LLMs utilizing retrieval-augmented generation (RAG), reinforcement learning (RL), and prompt engineering for engaging, contextually aware dialogues.Integrate AI components into autonomous agents capable of executing complex tasks such as scheduling, order management, and problem resolution.Design human-in-the-loop and automated systems for monitoring performance, identifying anomalies, and iteratively improving models based on real-world feedback.Develop pipelines for building knowledge graphs from business data, enhancing dynamic AI interactions.Collaborate with infrastructure teams to scale models effectively, ensuring robust performance and reliability.

About BasisBasis is a nonprofit organization dedicated to applied artificial intelligence research. Our mission is twofold: to understand and build intelligence and to advance society’s problem-solving capabilities. We strive to unravel the mathematical principles behind reasoning, learning, decision-making, understanding, and explanation, while also developing software that embodies these principles.Our commitment extends to enhancing our ability to tackle complex issues that are beyond today's capabilities and accelerating our potential to address future challenges. We are creating a technological framework inspired by human reasoning, alongside fostering a collaborative organization that prioritizes human values.About the RoleAs a Research Scientist, you will spearhead Basis’ initiatives to deepen our understanding of the conceptual, mathematical, and computational principles of intelligence. We seek individuals who excel technically and are passionate about exploring foundational concepts. Our research team values rigorous, high-quality scientific endeavors while encouraging experimentation and exploration of innovative ideas.Basis thrives on collaboration, both internally and with external partners. We are looking for team players who enjoy tackling significant problems that require collective effort.Research FocusDespite the growing acknowledgment that acquiring and understanding world models is crucial for intelligence, current AI systems face challenges in mirroring this human capability. Key uncertainties remain regarding the essence of a world model, methods for reliably detecting its presence in agents, and approaches to develop agents capable of learning these models effectively.Our research, particularly within the MARA project, seeks to establish new foundations and technologies for modeling, abstraction, and reasoning in AI systems. MARA's goal is to identify principled methods for how intelligence constructs, refines, and employs world models through interactive experimentation. Achieving this will require advancements in knowledge representation, abstraction, reasoning, active learning, and reinforcement learning, necessitating a first-principles reevaluation of world modeling.

About the Personalization Team Spotify’s Personalization team works to make discovering new music and podcasts easier and more enjoyable. Well-known features like Blend and Discover Weekly rely on a deep understanding of audio content to create recommendations tailored to each listener. These efforts reach millions worldwide, helping people find audio that fits their tastes. Role Overview The research group within Personalization leads advances in machine learning and artificial intelligence. The team explores new methods, questions established approaches, and shares findings with the broader research community. Senior Research Scientists here help set the direction for personalization technology and have a direct impact on Spotify’s product strategy and user experience.

Join Virtu Financial, a leading quantitative trading firm, where innovation meets impact in the financial markets. As a Machine Learning Researcher, you will engage in groundbreaking research opportunities within a dynamic and agile organization. This role presents a unique blend of intellectual challenge and immediate business influence, as you navigate complex problems that lack straightforward solutions.Your responsibilities will encompass our entire modeling ecosystem, from feature engineering and deep learning architecture to training dynamics and execution strategies. Your pioneering contributions will shape our market operations globally, making a real difference in a fast-evolving industry that thrives on creative problem-solving and first-principles thinking.We seek individuals with a strong sense of curiosity, a robust technical skill set, and a collaborative spirit, regardless of their industry background.

About ASAPP ASAPP develops AI technology to improve customer experience. Teams work with a focus on customer needs, clear goals, and measurable results. The company values ownership, purposeful speed, and ongoing improvement based on data and craft. ASAPP’s workforce spans New York City, Mountain View, Latin America, and India. The culture supports both hybrid and remote work, bringing together talent from around the world. Role Overview: Research Scientist, Conversational AI The research team is growing and seeks an experienced Research Scientist with expertise in Conversational AI and Machine Learning. This role focuses on solving scientific problems in Conversational AI and building domain-specific, real-world applications. The position involves working with large datasets from ASAPP’s products to investigate core research questions and deliver AI features that address practical needs.