AI Research Engineer - Alpha Discovery at Trexquant | New York

Join Trexquant as an AI Research Engineer, where you will be at the forefront of creating AI-powered systems that enhance alpha discovery for a forward-thinking quantitative hedge fund. In this pivotal role, you'll utilize state-of-the-art AI coding tools, such as Claude Code and other LLM-based agents, to develop automated research workflows that yield innovative data variables, predictive signals, and systematic trading strategies.Your work will bridge quantitative research, machine learning, and AI-enhanced development, resulting in scalable systems that significantly boost research efficiency and the quality of investment ideas.Key ResponsibilitiesDevelop AI-assisted research pipelines for data ingestion, feature engineering, alpha generation, and backtesting.Create autonomous workflows that explore datasets and propose potential signals.Quickly prototype and assess systematic strategies using comprehensive validation frameworks.Enhance research productivity by integrating AI coding agents into the quantitative workflow.Collaborate with researchers and Portfolio Managers (PMs) to transition validated alpha signals into production-ready applications.QualificationsProficiency in Python programming with experience in building research infrastructure.Strong foundation in statistics, machine learning, and backtesting methodologies.Practical experience utilizing AI coding tools (e.g., Claude Code, GPT-based agents) within a development workflow.Background in quantitative research, systematic trading, or alpha signal development is preferred.BenefitsCompetitive salary with performance-based bonuses.Friendly and collaborative work environment.Comprehensive PPO health, dental, and vision insurance fully covered for you and your dependents.Pre-tax commuter benefits.Weekly company meals.Applications are welcomed for both Stamford and New York City offices, with the NYC location set to open in October 2026.The base salary for this position ranges from $175,000 to $200,000, determined by the candidate’s educational background and experience. This role is classified as overtime-exempt.Trexquant is proud to be an Equal Opportunity Employer.

Join Trexquant as a dedicated Linux Systems Engineer, where you will play a pivotal role in constructing, managing, and scaling our on-premise infrastructure. This hands-on position emphasizes bare-metal Linux systems and offers significant ownership of server provisioning, storage management, and overall system reliability.The ideal candidate will be meticulous, highly disciplined, and adept at thriving in a challenging, production-critical environment. This role is specifically tailored for individuals with extensive experience in physical infrastructure, Linux internals, and automation within a high-performance context.Key Responsibilities:Construct, provision, and manage bare-metal Linux servers, overseeing OS installation, configuration, and lifecycle management.Take full ownership of server infrastructure from hardware through to the operating system and core services, ensuring optimal stability and performance.Configure and manage storage systems, including ZFS and enterprise storage platforms (e.g., NetApp, Dell, or similar).Monitor system health and performance, troubleshoot issues, and implement sustainable long-term solutions.Develop and maintain automation scripts using Ansible and Bash to standardize provisioning, configuration, and operational procedures.Conduct system patching, upgrades, and capacity planning across an expanding server fleet.Engage in incident response and root cause analysis, focusing on the continuous improvement of system reliability.Collaborate with engineering and infrastructure teams to optimize application performance on Linux systems.Contribute to documentation, runbooks, and operational best practices.Support data center operations as required, including hardware troubleshooting, racking, cabling, and server replacements.Occasionally travel to data centers for maintenance, expansions, and problem resolution.

Trexquant is a systematic fund focused on quantitative finance, with a team of researchers and engineers dedicated to advancing trading operations. The company is investing in its quantitative research and trading platform, aiming to shape the future of systematic trading. This early career Software Engineer role is based in New York and offers the chance to work alongside experienced engineers and quantitative researchers. The position centers on building and improving the infrastructure that supports systematic trading, including data pipelines, backtesting tools, and execution systems. Many projects involve greenfield development, offering opportunities to help design and implement new systems from the ground up. What you will do Develop low-latency, high-throughput research and trading systems using languages such as C++, C, Java, or Rust. Design and optimize data processing pipelines to ensure reliable access to large, high-quality datasets. Help create tools for backtesting, model training, and strategy evaluation. Work with researchers and traders to deliver technical solutions that support research and trading performance. Participate in code reviews, testing, and documentation to maintain high standards. Stay current with new technologies and best practices, contributing ideas to improve systems. Requirements Bachelor's or Master's degree in Computer Science or a related STEM field. Strong grasp of data structures, algorithms, and object-oriented programming. Proficiency in at least one programming language: C++, C, Python, Java, or Rust. Familiarity with Linux environments. Strong problem-solving skills and the ability to learn quickly in a team setting. Benefits Competitive salary with performance-based bonuses. Supportive and friendly workplace culture. Full coverage of PPO health, dental, and vision insurance premiums for employees and dependents. Pre-tax commuter benefits. Weekly company meals. Compensation The base salary range for this role is $130,000 to $175,000, depending on educational and professional background. Compensation may also include a discretionary, performance-based bonus. This position is overtime-exempt. Applications are open for both Stamford and New York City offices. The New York office is expected to open in October 2026. Trexquant is an Equal Opportunity Employer.

Trexquant is hiring a Senior Data Architect to lead the creation of a new data platform for quantitative research and simulation. This role centers on building a scalable system that unifies data from hundreds of vendors, ensuring reliable and accessible information for research and alpha generation across multiple asset classes. Key Responsibilities Design and implement a data platform that consolidates vendor datasets, offering consistent, high-quality access for research and simulation teams. Develop storage and retrieval solutions to support large-scale historical backtesting and high-frequency research. Create user-friendly interfaces and APIs, enabling researchers to discover variables, review metadata, and assemble standardized datasets for rapid idea testing. Work closely with quantitative researchers and simulation teams to understand their requirements and ensure the platform meets analytical and performance needs. Set standards for data modeling, normalization, version control, and quality assurance across diverse asset classes and sources. Partner with infrastructure and DevOps teams to enhance data pipelines, caching, and distributed storage for improved scalability and reliability. Prototype and launch internal tools that improve research efficiency and data transparency. Mentor data engineers, supporting well-documented and maintainable data systems. Platform Scope The platform will handle data for a broad range of financial instruments, including equities, futures, FX, ETFs, corporate bonds, and options. The focus is on transforming raw vendor feeds into structured, analysis-ready datasets that enable systematic research and backtesting. Location This position is based in New York, New York, United States.

Trexquant is on the lookout for an exceptional Senior Data Architect to spearhead the design and implementation of a cutting-edge architecture for our research and simulation data ecosystem. This pivotal role will unify Trexquant’s vast array of datasets—sourced from numerous vendors—into a streamlined, efficient, and scalable data platform that caters to simulation, research, and alpha generation across diverse asset classes.The ideal candidate will construct the comprehensive data infrastructure that empowers researchers and simulators to effortlessly discover, query, and integrate datasets spanning equities, futures, FX, ETFs, corporate bonds, and options. This role entails designing effective data models, storage solutions, and user-friendly interfaces that facilitate the transformation of raw vendor data into structured, analysis-ready formats, thereby enhancing systematic research and robust backtesting.ResponsibilitiesDesign and execute a unified data platform that consolidates hundreds of vendor datasets, ensuring consistent, accessible, high-quality data for simulators and researchers.Create efficient storage and retrieval systems to enable large-scale historical backtesting and high-frequency research workflows.Develop user-friendly interfaces and APIs that facilitate easy variable discovery, metadata exploration, and data assembly into standardized stocks × values matrices for rapid hypothesis testing.Work collaboratively with quantitative researchers and simulation teams to grasp their workflows, ensuring the data platform meets analytical and performance needs in real-world scenarios.Establish best practices for data modeling, normalization, versioning, and quality control across various asset classes and data vendors.Collaborate with infrastructure and DevOps teams to enhance data pipelines, caching mechanisms, and distributed storage for improved scalability and reliability.Prototype and deploy internal data applications aimed at bolstering research productivity and data transparency.Guide and mentor data engineers to uphold robust, maintainable, and well-documented data systems.

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.

At Trexquant, we are a pioneering systematic fund leading the way in quantitative finance, powered by a team of exceptional researchers and engineers. As we broaden our trading operations, we are committed to developing the next generation of our quantitative research and trading platform.We are looking for an enthusiastic Early Career Software Engineer with robust programming capabilities to join our dynamic engineering team. In this pivotal role, you will collaborate closely with seasoned engineers and quantitative researchers to design and enhance the infrastructure that drives our systematic trading, including data pipelines, backtesting tools, and execution systems. You will have the chance to engage in greenfield development projects, helping to construct new systems from the ground up and fostering innovation and scalability within our technology stack.

About BasisBasis is a pioneering nonprofit organization focused on applied AI research, driven by dual objectives.Our first goal is to comprehend and construct intelligence. We endeavor to lay down the mathematical principles defining reasoning, learning, decision-making, understanding, and explanation, while also developing software that embodies these principles.The second aim is to enhance society's capability to tackle complex challenges. We strive to broaden the scale, complexity, and diversity of problems we can address today, and more critically, to hasten our capacity to resolve future challenges.To fulfill these ambitions, we are creating an innovative technological foundation inspired by human reasoning, alongside a collaborative organization that prioritizes human values.About the RoleAs a Data Engineer on the Platform team at Basis, you will be responsible for constructing reliable data pipelines featuring comprehensive provenance and quality controls. You will curate documented datasets for training and evaluation while ensuring that our data infrastructure scales effectively. Your work will encompass both platform-specific data needs and cross-project data coordination, minimizing redundancy and fostering shared datasets.We are in search of technically proficient individuals who regard data quality as paramount. The ideal candidate has experience with machine learning data pipelines, understands the complete lifecycle from raw data to model training and evaluation, and approaches data provenance, lineage tracking, and quality assurance with rigor. You will blend software engineering best practices with a profound understanding of data systems and machine learning requirements.This role operates across both the Platform and Research teams, working on infrastructure that supports our commercial offerings and internal research initiatives. You will play a vital role in scaling Basis's data operations to support medium-scale models, ensuring data governance as we cater to external clients, and building systems that researchers can rely on for reproducible experiments.We seek individuals who are committed to executing high-quality, robust data engineering while remaining open to iteration, learning from real-world usage, and exploring diverse approaches to achieve excellence.At Basis, collaboration is key—both internally and with our external partners. We value those who enjoy laying the groundwork for solving grand challenges that extend beyond individual efforts.

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.

Join our dynamic Futures team as a Quantitative Researcher and leverage your skills in financial modeling and statistical analysis to develop innovative trading models. In this pivotal role, you will engage in research and model development focused on trading and risk management in the futures markets. We are looking for a proactive candidate with a strong grasp of market dynamics and a passion for data-driven decision-making.Key Responsibilities Create, implement, and enhance trading strategies to forecast trends in the futures market using comprehensive financial data and diverse trading signals. Analyze extensive datasets to uncover actionable alpha signals and formulate effective futures trading strategies. Research and apply leading academic insights in quantitative finance to evaluate and optimize the profitability of trading strategies. Drive continuous innovation by integrating new data sources and advanced methodologies to enhance model performance and scalability. Collaborate with a team of skilled quantitative researchers to conduct experiments, backtest theories, and refine strategies through thorough simulations and analytical rigor. Qualifications BS, MS, or PhD in a STEM discipline. A minimum of 2 years of experience in quantitative research, particularly in futures markets. A strong enthusiasm for machine learning and its applications in finance. Expertise in programming languages such as Python and proficiency in statistical modeling techniques. Excellent analytical and problem-solving capabilities. Effective collaboration skills, with the ability to work independently as well as in a team setting.

Trexquant is a dynamic systematic hedge fund leveraging advanced statistical algorithms to trade equities, futures, and various global markets. Our approach begins with extensive datasets, from which we create comprehensive feature sets and employ diverse machine learning techniques to identify trading signals, culminating in the formulation of market-neutral portfolios. We are on the lookout for innovative data scientists, physicists, engineers, economists, and programmers eager to contribute to the development of cutting-edge machine learning strategies that predict the movements of liquid financial assets with precision.The role of a Quantitative Researcher at Trexquant offers opportunities across several specialized teams:Alpha Researcher:Join the Alpha Researcher team to design and implement market-neutral signals, analyze large datasets, and collaborate with the Data and Strategy Research teams to create a diverse array of predictive models.Data Scientist:As part of the Data Science team, you will work on data parsing and analysis, sourcing new datasets, and teaming up with the Alpha and Strategy teams to build predictive machine learning models.Strategy Researcher:In the Strategy team, you will engage in the development of systematic strategies utilizing various machine learning and statistical methodologies, training and validating data derived from actual market trading.Upon applying for the Quantitative Researcher position at Trexquant, you will first be evaluated on the fundamental skills necessary for the role. Our interview process is designed to help us understand your strengths better and match you with a research team that aligns with your skills and preferences.Your Responsibilities:Design and optimize machine learning models aimed at predicting liquid asset movements using extensive financial datasets and a rich library of trading signals.Analyze data sets for future alpha development.Explore and implement cutting-edge academic research in quantitative finance.Collaborate with skilled quantitative researchers to conduct experiments and validate hypotheses through simulations.Requirements:BS/MS/PhD in a STEM field.Enthusiasm for machine learning.Proficiency in programming languages such as Python.Exceptional problem-solving abilities.Ability to function effectively both independently and as part of a team.Knowledge of financial accounting is advantageous.A background in quantitative finance is beneficial but not a prerequisite.Benefits:Competitive salary plus bonuses based on individual and company performance.

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.

About BasisBasis is a pioneering nonprofit organization specializing in applied AI research, dedicated to two interrelated goals.The primary objective is to comprehend and develop intelligence. This entails establishing the mathematical foundations of reasoning, learning, decision-making, understanding, and explanation; as well as creating software that embodies these principles.The secondary goal is to enhance society's capacity to tackle complex challenges. This involves broadening the scale and complexity of the problems we can address today and, more importantly, accelerating our future problem-solving capabilities.To realize these ambitions, we are constructing a new technological base inspired by human reasoning and fostering a collaborative organization that prioritizes human values.About the RoleAs a Research Engineer in Operations at Basis, you will be instrumental in developing internal tools, automation, and measurement systems that significantly enhance researcher productivity and operational efficiency. Your work will involve creating tools that eliminate hours of manual tasks, automating proposal and CRM workflows, and offering analytics to guide strategic decisions as Basis expands.We seek individuals who are technically adept and possess a deep understanding of research workflows, enabling them to pinpoint high-impact automation opportunities. An ideal candidate has experience in converting research concepts into reliable code, building automation systems powered by LLMs, and designing user-friendly tools for researchers. Your contributions will range from researcher productivity enhancements to GTM automation and analytics infrastructure.This position is vital to Basis's growth strategy, transforming operations from manual to automated processes that facilitate scalable growth with sustainable results.We are looking for innovative thinkers who are technically accomplished and eager to explore foundational concepts. Our research engineers strive to develop high-quality, robust tools, unafraid to experiment, learn from mistakes, and explore unconventional ideas to achieve their goals.Basis thrives on collaboration, both internally and with our partners; we seek individuals who are passionate about empowering others to achieve milestones they couldn't accomplish alone.

About the FellowshipPostdoctoral Fellowships at Basis provide a unique opportunity for distinguished researchers to advance their expertise in the field of computational intelligence. This encompasses areas such as reasoning, learning, and decision-making. Fellows will collaborate closely with Basis Research Scientists and esteemed Principal Investigators (PIs) from leading academic institutions.About BasisBasis is a nonprofit organization dedicated to applied AI research, driven by two interdependent goals.Our primary aim is to understand and develop intelligence. This involves establishing the mathematical foundations of reasoning, learning, decision-making, comprehension, and explanation; and creating software that embodies these principles.Secondly, we strive to enhance society's capability to tackle complex problems. This entails broadening the scope and complexity of challenges we can address today and, crucially, expediting our future problem-solving abilities.To fulfill these objectives, we are constructing a new technological framework inspired by human reasoning and fostering an innovative collaborative organization that prioritizes human values.How it WorksPostdoctoral Fellows at Basis are jointly mentored and funded by Basis and partner PIs from academic institutions. Fellows will divide their time between Basis and their academic PI's lab, functioning as part of a jointly advised postdoctoral program.Our established partner PIs include: Nada Amin (Harvard), Kevin Ellis (Cornell), Armando Solar-Lezama (MIT), Youssef Marzouk (MIT), and Tom Silver (Princeton).Each Fellow is paired with a mentor from Basis, chosen to align with their research interests and aspirations.Potential Basis mentors possess a wealth of expertise in various fields, ensuring a tailored and enriching mentorship experience.

About BasisBasis is a pioneering nonprofit organization specializing in applied AI research, dedicated to achieving two synergistic objectives.The first objective is to comprehend and develop intelligence. This encompasses establishing the mathematical foundations of reasoning, learning, decision-making, understanding, and explanation; subsequently, we construct software that embodies these principles.The second objective is to enhance society's capacity to tackle complex issues. This involves broadening the scope, intricacy, and variety of challenges we can address today, while also accelerating our future problem-solving capabilities.To fulfill these ambitious goals, we are creating a robust technological foundation inspired by human reasoning, alongside a collaborative organization that prioritizes human values.About the RoleWe are in search of a Technical Program Manager who possesses a deep passion for program management and is eager to propel ambitious research initiatives. In this role, you will be the crucial link connecting our researchers, engineering teams, leadership, and external partners, requiring both technical acumen and project management skills.

Kepler: The AI you can trust and verify.Every AI tool has inherent flaws: the model interacts with data, leading to inaccuracies—be it fabricating sources or providing inconsistent answers. For those making crucial million-dollar decisions, this isn’t just a flaw; it's a dealbreaker.At Kepler, we have engineered an architecture that makes hallucination structurally impossible. Our AI interprets your intent while deterministic code retrieves precise figures from source documents. The model never generates arbitrary numbers, ensuring every output can be traced back to a filing, a page, or a line item, with every calculation clearly showing its formula. This guarantees defensibility in all answers.In production, we handle over 950K SEC filings, 14K+ companies, and 40M+ documents across 27 global markets, trusted by firms that can't afford to be wrong.Our architecture is domain-independent, starting with finance where the pain points are most acute, and extending to healthcare, legal, and insurance sectors. We’re not just creating a finance product; we're building the verification layer for the entire AI ecosystem.Founded by Vinoo Ganesh (7 years at Palantir, former Head of Business Engineering at Citadel) and Dr. John McRaven (11 years at Palantir, creator of the analytics engine behind $100M+ contracts with BP and Airbus, Ph.D. in Physics). We are backed by the founders of OpenAI, Facebook AI Research, MotherDuck, dbt, and Outerbounds.The RoleAs the Head of AI Research, you will set the research agenda to ensure AI is trustworthy for enterprise decision-making. At Kepler, we’ve tackled hallucination not by enhancing model intelligence but by designing systems where such issues cannot occur. AI interprets intent, and code retrieves data, linked through a semantic layer. Every output is directly traced to its source.We are seeking an innovative leader to advance the boundaries of what is achievable within this architecture.You will spearhead research in agentic systems, memory architectures, retrieval techniques, and evaluation frameworks. You will have access to unique financial data, including structured filings, earnings transcripts, market feeds, research reports, and live audio—all normalized with full provenance. This isn't another lab creating demos; your contributions will directly impact production, empowering financial professionals who make high-stakes decisions.This position is perfect for researchers eager to develop AI systems that operate effectively in high-stakes environments, where every answer is substantiated and every insight can be traced back to the truth.

Trexquant is a premier systematic hedge fund that employs cutting-edge machine learning and quantitative strategies to maintain a market-neutral portfolio. With a global presence spanning the U.S., China, and India, our innovative team of researchers, technologists, and finance experts is dedicated to advancing the field of quantitative finance.We are on the lookout for a motivated and detail-oriented Business Development and Strategy Associate to enhance our growing statistical arbitrage hedge fund. In this role, you will collaborate closely with the Chief Strategy Officer to identify new business opportunities, implement initiatives for process and product improvements, and drive the firm's growth through data-centric decisions. The ideal candidate will demonstrate robust analytical and project management abilities, along with an entrepreneurial mindset to expand our market presence and reinforce our competitive advantage.

About BasisBasis is a pioneering nonprofit organization dedicated to applied AI research, driven by two interlinked objectives.The first goal is to comprehend and construct intelligence. This involves establishing the mathematical foundations of reasoning, learning, decision-making, understanding, and explanation, alongside developing software that embodies these principles.The second objective is to enhance society's capacity to tackle complex challenges. This entails broadening the range, complexity, and scope of problems we address today, while importantly expediting our future problem-solving capabilities.To realize these ambitions, we are establishing a novel technological foundation inspired by human reasoning, as well as a unique collaborative organization that prioritizes human values.About the RoleAs a Research Engineer on the Platform team at Basis, you will propel research methodologies forward and package them into modular components for reuse by others. Your responsibilities include developing core technology modules (such as ChiRho, Effectful, Weighted), enhancing research-backed features for commercial platforms, and ensuring that research advancements lead to tangible impacts—both commercially and socially.We are seeking individuals who can merge research excellence with engineering precision. The ideal candidate has a background in both published research and production code, possesses the ability to translate experimental techniques into solid implementations, and thoughtfully approaches software architecture to facilitate others in building upon your contributions. You will identify high-impact research challenges aligned with Basis's mission and guide them from conception to concrete execution.This position is distinct from Operations Research Engineers (who concentrate on internal tools) as it emphasizes advancing research methods for platform and commercial applications. You will collaborate on Core Tech Module Teams and contribute to research that shapes the technological bedrock of Basis.We value individuals who excel at technical tasks and are unafraid to delve into foundational concepts. Our research engineers strive for thorough, high-quality, robust science and engineering, while embracing experimentation, learning from mistakes, and exploring unconventional ideas to achieve their goals.Basis thrives on collaboration, both internally and with our external partners; we seek individuals who enjoy working collectively on challenges that exceed individual capabilities.

At Yotpo, we are pioneering the future of trust and loyalty in eCommerce. Leveraging our AI-driven Reviews and Loyalty solutions, we empower brands to convert casual browsers into loyal customers and passionate advocates. With robust integrations throughout the eCommerce landscape and the confidence of over 30,000 global brands, Yotpo crafts seamless omnichannel experiences that enhance conversion rates, foster customer relationships, and promote sustainable growth.If you've ever utilized ChatGPT or Perplexity for shopping inquiries, you've experienced the next evolution of eCommerce, where Large Language Models (LLMs) influence how consumers engage with brands. This is the mission of Yotpo Discover, where we are committed to enhancing brand visibility.We are currently seeking an AI Marketing Researcher to position Yotpo as an authority in the rapidly evolving domain of AI-driven discovery.This hybrid role merges research, product marketing, and storytelling. You will collaborate closely with Product, Customer Success, and clients to transform real data and outcomes into valuable insights, narratives, and evidence that educate the market and bolster pipeline growth.

Antimetal is on the lookout for a Research Engineer to enhance the intelligent systems that drive our innovative solutions. In this role, you'll be tasked with prototyping cutting-edge methodologies, conducting experiments, and overseeing the transition from research to real-world application. Collaboration with our platform and product teams will be key as you help shape the capabilities of our AI agents and contribute to the development of evaluation methodologies.Modeling infrastructure and its observability is a challenging domain. The telemetry we handle is often high-volume, chaotic, and transient, with ground truth that is often only approximate. Our goal is to develop AI agents capable of understanding this intricacy and reasoning about operational dynamics, including implementing code and configuration modifications.Research Focus AreasInfrastructure Intelligence: Developing models to comprehend infrastructure behaviors and the underlying reasons, such as anomaly detection, issue forecasting, telemetry analysis across logs, metrics, events, and traces, and understanding causal relationships. These foundational capabilities enable our agents to reason effectively about infrastructure.Autonomous Agents: Designing long-running, parallel agents that can identify, diagnose, and remediate infrastructure problems, including the ability to fix code and configuration issues. Enhancements in multi-step reasoning, orchestration, context management, memory, and reinforcement learning will be essential for this role.Evaluation: Ensuring the performance of our agents and guiding improvements by collaborating with the platform team to establish evaluation methodologies, generate synthetic data, analyze past incidents, and model the domain.About AntimetalAntimetal aims to redefine the future of infrastructure management. Our mission is to create a platform that identifies, resolves, and prevents issues, allowing engineers to focus on what they excel at: developing exceptional products.Your Responsibilities:Experiment, Evaluate, Iterate, Ship: Conduct experiments across our research domains, analyze outcomes, validate effective methods, and transition successful strategies into production.Build Evaluation Infrastructure: Work alongside the platform team to establish live and offline evaluation systems, benchmarks, and synthetic data generation tools that facilitate continuous improvement.