Campus Recruiter

About the Position Jane Street is seeking a talented Campus Recruiter who will play a pivotal role in shaping our recruitment strategy and expanding our efforts to attract, interview, and onboard exceptional interns and new graduates for our Research and Machine Learning Research teams. This position will involve planning, organizing, and executing our inter…

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.

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 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 CampusCampus is transforming the landscape of higher education with a bold mission: to accelerate the development of tomorrow's talent and redefine the college experience for today’s aspiring students. As college expenses soar, the outcomes remain stagnant, leaving students in a lurch. We believe that traditional education must evolve to meet the ambitions of modern learners who cannot afford to wait.At Campus, we offer a cutting-edge, accredited two-year college program where students engage with esteemed professors from top-tier universities such as Princeton, Stanford, and Howard through dynamic, live online classes. Our graduates emerge equipped with essential business and AI skills, prepared to embark on their careers or transfer to prestigious four-year institutions. Our innovative approach is built upon a state-of-the-art technology platform and a meticulously researched model of student success that ensures each learner receives personalized guidance and on-demand academic support. We are honored to be recognized as one of Fast Company's Most Innovative Companies of 2024.Supported by an exceptional group of investors who share our passion for the future of education—including General Catalyst, Founders Fund, Bloomberg Beta, 8VC, Rethink Education, and notable figures like Sam Altman and Shaquille O’Neal—we are poised to lead the charge in educational innovation.As the landscape of higher education evolves, we are at the forefront of change. Join us in shaping the future!About the RoleWe are in search of a Senior Staff AI Research Engineer who is passionate about making Campus the leading organization in AI-driven learning. This pivotal role calls for extensive technical expertise in machine learning and a fervor for creating innovative systems that enhance and personalize the student experience. You will spearhead research initiatives, develop production-ready AI features, and contribute to scholarly publications that push the boundaries of AI in education.Your Journey with Us Will Involve:Designing and developing groundbreaking AI systems to enrich the Campus learning experienceConducting thorough experiments to validate the efficacy of these systems...

About the Position Jane Street is seeking intelligent and inquisitive minds to join our expanding Machine Learning team and lead our innovative ML initiatives. As a Machine Learning Researcher, you will develop advanced deep learning models that enhance our trading strategies, supported by our powerful computing cluster featuring tens of thousands of high-performance GPUs. The trading landscape presents unique challenges—such as complex models and dynamic datasets within a competitive multi-agent setting—driving us to explore cutting-edge methodologies. At Jane Street, our researchers, engineers, and traders collaborate closely, often just a few feet apart, to train models, design systems, and execute trading strategies. Each day may involve analyzing market data, optimizing hyperparameters, troubleshooting distributed training performance, or assessing our models' real-world trading behavior. Your extensive knowledge of the machine learning ecosystem and familiarity with diverse methodologies—ranging from LLMs, image models, reinforcement learning agents, recommendation systems, to classical ML techniques—will be instrumental in shaping the future of ML at Jane Street. You will be responsible for training models that will inform the next generation of our deep learning-driven trading strategies, as well as building the foundational insights necessary for navigating new markets and situations. Additionally, you will engage in hiring new talent, attending conferences, and sharing knowledge with teammates—all considered vital aspects of your role.

Why Join Our Team At Seven Research, we tackle the unsolved challenges in technology and science. Our passionate team of innovators thrives on pushing the limits of what is possible in the global markets. We provide cutting-edge resources and foster an environment of intellectual freedom, empowering our team to create pioneering solutions to the most intricate problems in our domain. Our collaborative culture values excellence from all members, regardless of their experience level. Your Role As a Deep Learning Researcher, you will be at the forefront of advancing quantitative finance through the design and development of sophisticated deep learning models. Your role will involve conducting thorough and methodical research to establish groundbreaking methodologies, reveal complex insights, and integrate innovative strategies within our teams. What We Seek We are in search of skilled and knowledgeable problem-solvers with a robust background in deep learning to join our team. No prior financial knowledge is necessary. Candidates for the Deep Learning Researcher position should demonstrate exceptional applied research and analytical skills. We appreciate team members who communicate effectively and take initiative in their projects. If you are excited about tackling challenging quantitative problems in a research-oriented environment, we would love to meet you. The ideal candidate will possess most of the following qualifications: PhD in Computer Science or a related field Expertise in deep learning techniques with a proven history of developing advanced predictive models Publications in relevant academic journals and/or conference presentations Proficient programming skills, particularly in Python Excellent problem-solving abilities and research proficiency Strong communication skills for conveying complex technical concepts Experience with large datasets and computationally intensive projects Familiarity with high-performance computing

Join Our Innovative TeamAt Seven Research, we tackle unsolved challenges in the global markets, driven by a passionate team dedicated to advancing technology and scientific exploration. Our collaborative environment nurtures intellectual freedom and provides cutting-edge resources, empowering our employees to create pioneering solutions to the most intricate problems in our industry.Your ContributionAs a Quantitative Researcher, you will be the visionary behind our trading strategies, crafting advanced models that convert complex datasets into valuable insights. You will employ rigorous statistical analysis and machine learning techniques on diverse financial information, pioneering new methods to assess risks and returns while creating strategic frameworks based on foundational economic principles.Ideal Candidate ProfileWe are seeking driven and talented problem-solvers with a solid quantitative foundation. No prior financial knowledge is required. Candidates for the Quantitative Researcher position should have a proven ability to perform innovative research and analytical work. We appreciate individuals who communicate effectively, possess strong analytical skills, and take ownership of their projects. If you thrive on solving challenging quantitative problems in a supportive environment, we want to meet you.The ideal candidate will have most of the following qualifications:PhD, Master’s, or Bachelor’s degree in computer science, statistics, physics, or a related quantitative discipline.Demonstrated experience in developing advanced predictive models.Proficient programming skills, particularly in Python for data analysis.Familiarity with statistical and machine learning frameworks.Strong analytical and problem-solving abilities.Effective communication skills to explain complex technical concepts clearly.Experience with large datasets and computationally demanding projects.

About the PositionJane Street is seeking talented Quantitative Researchers to assist in developing models, strategies, and systems for pricing and trading financial instruments. You will collaborate closely with seasoned researchers dedicated to mentoring our newest team members, immersing yourself in experimental design, dataset generation, time series analysis, feature engineering, and model construction for financial datasets.At Jane Street, our researchers, engineers, and traders work in close proximity, fostering a collaborative environment to train models, design systems, and execute trading strategies. We leverage petabytes of data and operate on a computing cluster with hundreds of thousands of cores, alongside a rapidly expanding GPU cluster featuring tens of thousands of high-performance GPUs. Your daily tasks may include delving into market data, fine-tuning hyperparameters, debugging distributed training performance, or analyzing our model's trading behavior in production settings.We reject the notion of a “one-size-fits-all” modeling approach; instead, we embrace a wide array of statistical and machine learning techniques, from linear models to deep learning, adapting our methods to meet the specific needs of each problem. The most successful researchers thrive on their curiosity about how their contributions integrate into the broader framework of our trading operations, transforming their findings into actionable strategies.About YouIf you’ve never considered a career in finance, you’re not alone—many of our team members were in the same boat before joining us. If you possess a curious mind and a passion for tackling intriguing challenges, you will likely feel at home here. Ideal candidates will:Utilize logical and mathematical reasoning to approach diverse problemsExhibit intellectual curiosity; eager to ask questions, acknowledge mistakes, and pursue new knowledgeBe proficient in programming, particularly with PythonCommunicate precisely and think openly, enjoying collaboration with colleagues across various fields and expertiseWhile most candidates have a background in data science or machine learning, we prioritize your thought process and learning capability over specific knowledge. A PhD or relevant research experience is advantageous.For more insights, feel free to explore our interview process and meet some of the team.

Position OverviewJane Street is seeking talented Quantitative Researchers to join our innovative team. In this role, you will develop advanced models, strategies, and systems for pricing and trading financial instruments. Your expertise in experimental design, dataset generation, time series analysis, feature engineering, and model building will be applied to financial datasets, all while collaborating with a team of experts who will challenge and enhance your methodologies.At Jane Street, our researchers, engineers, and traders work closely together in a dynamic environment, leveraging petabytes of data and a vast GPU cluster equipped with tens of thousands of high-performance GPUs. Your day might involve deep analysis of market data, tuning hyperparameters, debugging distributed training issues, or evaluating how our models perform in real-world trading scenarios.We value diversity in our modeling solutions, embracing a broad range of statistical and machine learning techniques, from linear models to deep learning, tailored to meet the unique challenges we face. The most successful researchers will possess a strong curiosity about how their work contributes to our trading operations and how to translate their insights into actionable strategies.

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.

At Trexquant, a cutting-edge systematic hedge fund, we leverage a multitude of statistical algorithms to navigate global equity, futures, and other markets. Our approach harnesses extensive datasets to create comprehensive feature sets, utilizing advanced machine learning techniques to unearth trading signals and integrate them into market-neutral portfolios. We are actively seeking talented individuals from diverse backgrounds, including data science, physics, engineering, economics, and programming, to pioneer the next wave of machine learning strategies that adeptly forecast the movements of liquid financial assets.As a Quantitative Researcher, you will engage in the development of market-neutral signals, meticulously parse and analyze large datasets, and collaborate with the Data and Strategy Research team to construct a variety of predictive models. While we welcome expertise across all asset classes, our immediate focus lies on equities, futures, commodities, and event-driven research.

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.

Start Dates Available: Immediate StartAbout AlphaSightsAt AlphaSights, we unite ambitious individuals from around the world to collaborate with premier investment firms, strategy consultancies, and Fortune 500 companies. Our mission is to empower clients by connecting them with niche experts, enhancing their decision-making capabilities, and driving forward momentum.Since our inception in 2008, we've experienced remarkable growth, establishing ourselves as a leader in the knowledge management sector with over 1,500 professionals across nine cities globally. Our commitment to excellence compels us to seek only the most talented graduates to help us scale new heights.About This RoleAs a Campus Recruiting Manager at our New York office, you will be instrumental in shaping our recruitment strategies and processes to attract and hire exceptional entry-level talent. You will lead a team of junior recruiters and coordinators, devising and implementing initiatives that engage early career candidates and foster their development within our rapidly growing organization.We seek a dynamic and innovative recruiting professional who thrives in a fast-paced environment, is passionate about mentoring others, and is driven to make a significant impact by meeting our high-volume hiring needs.

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.

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.

Quick FactsRole: Quantitative ResearcherLocation: 5 days/week @ NYC HQBase Salary: $200K to $325KEquity: Competitive initial grant plus annual performance-based bonusesAbout MomentMoment is at the forefront of developing innovative trading and portfolio management technology. Our flagship product suite encompasses high-throughput market data pipelines, automated smart order routing algorithms, real-time portfolio ledgering and position tracking, as well as advanced portfolio optimization techniques.Founded in 2023 by a dynamic team of quantitative traders and researchers from Citadel and Jane Street, we have successfully secured over $100 million in funding from notable investors including Andreessen Horowitz and Index Ventures. Our technology supports critical operations for financial institutions managing assets exceeding $8 trillion.The Research Team at Moment tackles complex challenges such as:Executing over 100K variable portfolio optimizations within seconds.Creating machine learning models to predict relative value and future performance of fixed income securities.Formulating risk models to assess the tracking error across portfolios.Developing AI agents to conduct credit research, construct custom portfolios, and automate essential portfolio management functions.You're a Great Fit If...You are a quantitative researcher or trader, with a willingness to consider strong candidates from other fields.You possess a bachelor's degree or PhD in Mathematics, Physics, Statistics, Economics, or Computer Science.You have experience writing production-ready code in Python.You are resourceful and eager to tackle challenges.You enjoy collaborating closely with clients; at Moment, researchers also act as product managers.Preferred QualificationsExperience in fixed income quantitative research.Familiarity with numerical optimization techniques.Knowledge of factor and risk models.Experience with Polars.Proficiency in machine learning pipelines.Experience with multi-modal LLMs.BenefitsHealth Insurance401k

Join Virtu’s Research Technology team as an accomplished Machine Learning Engineer. You'll be part of a dynamic group of specialists focused on creating the robust infrastructure that fuels our quantitative researchers. This is a rare chance to engage at the crossroads of machine learning and systematic trading, developing tools that directly influence the efficiency and speed of our research capabilities. In this pivotal role, you will spearhead the development of our machine learning research platform. Your responsibilities will include managing data and computational resources, tracking experiments, and empowering researchers to transition from concept to result with maximum efficiency. Collaborating closely with quantitative analysts and engineers, you will significantly impact the implementation of machine learning practices as we enhance our operational capabilities. Our tech stack primarily includes Python, C++, and Java, complemented by various open-source tools and proprietary technologies.