Two Sigma is a leading quantitative investment management and trading firm. The company applies a scientific approach to investing, combining cutting-edge technology, artificial intelligence, data science, and quantitative research with rigorous human inquiry to capitalize on market opportunities and deliver alpha for investors.

Our team of engineers, quantitative researchers, and data scientists looks beyond the traditional to test hypotheses and develop creative solutions to some of the world’s most complex economic problems.

We are looking for creative experts who are interested in applying general Machine Learning and specifically Deep Learning (complex neural networks, sequence models etc.), Large Language Models, Reinforcement Learning techniques to many types of problems in complex systems, but particularly those with large amounts of noisy data.

This role is only open to MS with work experience and PhDs, both in their final year of study.

You will take on the following responsibilities:

-Develop effective techniques and infrastructure, from the initial idea to the running prototypes and productionization

-You will write code, use the latest AI and Machine Learning tools, run experiments on state-of-the-art infrastructure and in the cloud, and generally develop techniques and processes to build predictive models for financial markets including but not limited to alpha modeling and trading tactics

-Partner with teams across Two Sigma to implement your ideas into our products

-Remain connected to the broader research community by partnering with internal and external collaborators and participate in relevant conferences

You should possess the following qualifications:

-Advanced degree in Computer Science, Engineering, or other STEM field, preferably in a PhD program, or in a Master’s program with some prior work experience

-Excellent programming skills in Python (familiarity with Rust/Java/C++ is a plus) and deep knowledge of Tensorflow/PyTorch/JAX or similar

-Internships/work experience with Deep Learning, LLMs and/or Reinforcement Learning

-Background in Machine Learning techniques with large amounts of noisy data, curiosity in applying it to financial problems

-Relevant research experience (publications at NeurIPS, ICML, ICLR or similar are preferred)

-Experience with cloud environments and multi-machine CPU/GPU setups

-Experience with version control systems, regression/unit testing, code reviews, profiling

-Participation in open source community is a plus

-Being able to work well with others in teams

You will enjoy the following benefits:

-Core Benefits: Fully paid medical and dental insurance premiums for employees and dependents, competitive 401k match, employer-paid life & disability insurance

-Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms Learning: Tuition reimbursement, conference and training sponsorship

-Time Off: Generous vacation and unlimited sick days, competitive paid caregiver leaves

-Hybrid Work Policy: Flexible in-office days with budget for home office setup

Two Sigma is a leading quantitative investment management and trading firm. The company applies a scientific approach to investing, combining cutting-edge technology, artificial intelligence, data science, and quantitative research with rigorous human inquiry to capitalize on market opportunities and deliver alpha for investors.

Our team of engineers, quantitative researchers and data scientists looks beyond the traditional to test hypotheses and develop creative solutions to some of the world’s most complex economic problems. When you work with us, you tackle tough problems alongside other scientists and engineers. People who will challenge your ideas. Who you can really learn from, and collaborate with. And you’ll be doing work that matters to a lot of people, too. Our investors include some of the world’s largest retirement funds, research institutions, educational endowments, healthcare systems and foundations. We admire what they do, and we’re proud to serve these organizations.

You will take on the following responsibilities:

-Use the scientific method to develop sophisticated investment models and shape our insights into how the markets will behave

-Apply quantitative techniques like machine learning to a vast array of datasets

-Create and test complex investment ideas and partner with our engineers to test your theories

-All the while, you’ll remain engaged in the academic community. As examples, you can:

-Join our reading circles to stay up to date on the latest research papers in your fields

-Attend academic seminars to learn from thought leaders from top universities

-The internship program lasts 10 weeks in the summer and takes place at our Soho-based, New York City office. You will partner with an assigned mentor and work on a single project during the course of your time here, which will culminate in a final presentation at the conclusion of the program.

You should possess the following qualifications:

-Are pursuing a degree in a technical or quantitative disciplines, like statistics, mathematics, physics, electrical engineering, or computer science with approximately one year remaining in your programs (all levels welcome, from bachelor’s to doctorate)

-Demonstrate intermediate skills in at least one programming language (like C, C++, Java, or Python)

-Performed an in-depth research project, examining real-world data

-Are an independent thinker who can creatively approach data analysis and communicate complex ideas clearly

-You don’t need a background in finance. It’s nice to have, but more than half of Two Sigma’s employees come from outside the finance industry. If you’ve got the quantitative skills, we can teach you the financial aspects of the job.

You will enjoy the following benefits:

-Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms

-Hybrid Work Policy: Flexible in-office days

About Snorkel

Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes.

About the Role

Snorkel AI is hiring Forward Deployed Researchers (Multiple levels) who will partner with frontier AI labs on their most challenging data problems. This is a high-impact, customer-facing role that combines deep technical and research credibility with the ability to work directly with customer research teams. You'll partner with customer research teams to design complex data and environments that improve frontier model performance, serving as a thought partner throughout the engagement.

You'll work at the critical intersection of research, technical strategy, and customer partnership. This includes scoping training data needs, designing RL environments and tasks, developing evaluation frameworks, probing model behavior and failure modes, and translating customer research objectives into actionable technical plans.

Forward Deployed Researchers own a technical domain. You are the person who knows where frontier models fail in it, what data moves those numbers, and what we should build next.

Main Responsibilities - Own a technical domain end to end: the technical bar for what we build in it, and what we build next - Partner with frontier AI research labs to design datasets and environments that improve model performance - Lead technical conversations with customer researchers to understand model capabilities, failure modes, data requirements, and success criteria - Probe model behavior through systematic evaluation to uncover weaknesses and identify high-impact data interventions - Benchmark frontier models against our datasets to demonstrate value to customers, building or adapting evaluation harnesses as needed, and turn the results into pass-rate analysis, failure-mode breakdowns, and purchase recommendations - Design evaluation frameworks, calibration processes, and quality rubrics that establish measurable project success metrics - Develop technical specifications for data projects that balance research rigor with operational feasibility - Hold the demand shape for your domain: which labs want what, at what volume, against what bar, and where the asks are converging - Develop a point of view on where your domain is heading, and partner with Research on what should exist before a customer asks for it - Serve as thought partner to customer research teams throughout the sales cycle, building trust and credibility - Stay current on frontier AI research, RL environment design, post-training techniques, and evaluation methodologies

Preferred Qualifications - Strong expertise in frontier AI concepts including LLMs, training data pipelines, evaluation methodologies, post-training techniques (RLHF, DPO, RLAIF), and domain areas such as coding agents, reasoning, multimodal models, or RL environments - Experience in applied ML research, data science, or research-intensive technical roles - Customer-facing or collaborative research experience, or demonstrated aptitude for client engagement - Proficiency in Python, familiarity with ML frameworks and LLM APIs, and comfort running evaluations in containerized environments - Excellent communication skills, ability to deliver technical presentations and explain complex concepts to diverse audiences - Familiarity with data curation workflows, synthetic data generation, LLM-as-a-Judge, or evaluation framework design - Willingness to make and state a defensible assumption when a request arrives underspecified, rather than waiting for the customer to close the gap - Ability to work in a fast-moving environment

Introduction

Join the pioneering AI Foundations Research team at IBM Research and contribute to shaping the future foundations of artificial intelligence. Our group of scientists, engineers, and designers is dedicated to conducting end-to-end research that delivers real-world AI impact through a rigorous, responsible, and open innovation framework. We are the team behind IBM's Granite open-source models, and our work spans multi-modal (vision, speech, language, code) and multi-lingual systems, data quality, data generation, novel model architectures, training recipes, governance and trustworthiness, and programming models for interacting with models. As an intern, you will explore cutting-edge research areas, including new algorithms for training, fine-tuning, reinforcement learning, and inference time scaling, alongside pioneering work in generative computing and generative programming for language, code, and other modalities, all within a collaborative environment that bridges fundamental science and transformative engineering.

Your role and responsibilities

As an AI Research Scientist Intern, you will engage in the full research lifecycle to pioneer new advancements in artificial intelligence. Your role will involve identifying core challenges, designing novel prototype solutions, and validating them through rigorous experimentation. You will conduct foundational research in critical areas such as novel training algorithms, efficient fine-tuning, reinforcement learning, and inference-time scaling for multi-modal models. Collaborating in small, mentored teams, you will be responsible for shepherding projects from ideation to completion. A key objective is to disseminate significant results through publications in leading conferences and patent applications, contributing to both the academic community and IBM's open innovation initiatives.

Required education

Bachelor's Degree

Preferred education

Master's Degree

Required technical and professional expertise

• Research Experience with Modern ML: Hands-on experience with and a deep theoretical understanding of Large Language Models (LLMs), Vision-Language Models (VLMs), and Transformer-based architectures.
• Strong Programming & Prototyping Skills: Proficiency in Python for rapid prototyping, experimental setup, and implementing large-scale machine learning systems.
• Rigorous Analytical & Problem-Solving Abilities: Demonstrated strength in quantitative analysis, designing experiments, and deconstructing complex research problems.
• Proven Research & Communication Skills: A track record of innovation (evidenced by peer-reviewed publications or strong preprints) and the ability to clearly articulate complex technical concepts in both writing and presentations.
• Collaborative Research Mindset: A team-oriented approach with a commitment to rigorous, reproducible, and well-documented research practices.

Preferred technical and professional experience

• Research Excellence: Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, AAAI).
• Technical Proficiency: Advanced expertise in ML frameworks (PyTorch) and full-cycle development of algorithms and systems.
• Specialized Skills: Hands-on experience with generative AI (LLMs) and multimodal models, from training to testing.
• Communication: Demonstrated ability to present complex research and build high-impact technical demonstrations.

Location NYC, USA

Why Work with Us

Solve impactful problems. At Seven Research, our close-knit team unites brilliant minds passionate about pushing technological and scientific boundaries in the global markets. We provide state-of-the-art resources and cultivate intellectual freedom, enabling our people to develop groundbreaking solutions to the most complex challenges of our field. Our collaborative approach celebrates excellence from everyone, regardless of tenure.

Your Role

Core Developers are at the heart of our technological ecosystem, working to continuously optimize our research and technological infrastructure. In this role, you will build key components to accelerate our trading operations, design scalable systems and tools that support high-performance computing, and ensure that our systems provide the speed and robustness necessary to maintain our edge. You will be challenged to produce elegant and efficient code every day. You will also conduct in-depth research and testing relating to performance optimization, networking architecture, and hardware selection. If you are excited by the prospect of solving these sorts of problems in a collaborative, research-driven environment, we would love to get to know you.

What We’re Looking For

We seek talented engineers who approach problems with a holistic, innovative mindset. No financial knowledge is expected. You should have excellent programming and analytical skills and be excited to apply these talents within our state-of-the art research and trading infrastructure. You should be motivated to take ownership over core projects and always ready to identify and resolve inefficiencies. You should be continuously guided by the question: how can this work better?

The ideal candidate will possess most of the following:

• PhD, master’s, or bachelor’s degree in computer science or a related field
• Strong background in data structures and algorithms, object-oriented programming, and mastery of C++
• Experience with latency-sensitive development and low-level system architecture
• Advanced knowledge of high-performance computing, distributed system design, and network optimization
• Strong problem-solving skills and research acumen
• Strong communication skills to articulate complex technical concepts

Job Compensation Range

The base salary range for this role is prorated based on the full-time salary range of $200,000 - $300,000. This does not include other forms of compensation and benefits that are part of Seven Research’s comprehensive package. We will provide additional detail about compensation and benefits during our hiring process.

Accommodations

If you need a reasonable accommodation to participate in any part of our application or interview process, please contact careers@sevenresearch.com. We’ll work with you to support your participation.

We are an equal opportunity employer and prohibit discrimination and harassment without regard to race, religion, age, sex, or any other characteristic protected by law.

If you have any questions, please contact us at careers@sevenresearch.com.

Locations: London, United Kingdom; New York, NY, United States

Hudson River Trading (HRT) is hiring an AI Researcher to join the HAIL team. HAIL (HRT AI Labs) is the team at HRT responsible for developing and maintaining our most powerful models, which are used by our trading teams to drive a significant fraction of our trading. We are building and deploying "foundation models for markets", that ingest and train on vast amounts of market data, to make predictions about future market state. We are seeking experienced AI researchers to join our team to accelerate our efforts.

Researchers have great independence to pursue the research directions they think would be most impactful as part of a small focused team with minimal bureaucracy. They are enabled by state-of-the-art research clusters with very high GPU-to-researcher ratios, and supported by excellent engineering, hardware, and systems teams to realize their vision. Your work will be directly, clearly, highly impactful on the business, and it will be challenging: this is a field with no easy or obvious solutions. You'll be responsible for improving every part of our models: from featurization of data, to architecture design, to training dynamics, to how trading decisions are made.

Qualifications

Must have two or more years work experience in deep learning research, for any domain: robotics, biology, chemistry, physics, audio, video, etc. Experience translating methods between areas of application is highly valued. LLM experience is valuable, but not necessary. Strong engineering skills valued, especially any of: GPU kernel development, lower-level Pytorch/JAX development, intermediate C++, FPGA/ASIC experience, HPC experience. The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience.

This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package which includes medical, dental, vision, basic life insurance, and enrollment in our company’s retirement savings plans. Employees will receive sick and parental leave, as well as other paid time off (including 20 vacation days and 10 paid holidays in the US). Please note that benefits and time off policies will vary across non-US locations.

Culture

Hudson River Trading (HRT) brings a scientific approach to trading financial products. We have built one of the world's most sophisticated computing environments for research and development. Our researchers are at the forefront of innovation in the world of algorithmic trading.

At HRT we welcome a variety of expertise: mathematics and computer science, physics and engineering, media and tech. We’re a community of self-starters who are motivated by the excitement of being at the cutting edge of automation in every part of our organization—from trading, to business operations, to recruiting and beyond. We value openness and transparency, and celebrate great ideas from HRT veterans and new hires alike. At HRT we’re friends and colleagues – whether we are sharing a meal, playing the latest board game, or writing elegant code. We embrace a culture of togetherness that extends far beyond the walls of our office.

Feel like you belong at HRT? Our goal is to find the best people and bring them together to do great work in a place where everyone is valued. HRT is proud of our diverse staff; we have offices all over the globe and benefit from our varied and unique perspectives. HRT is an equal opportunity employer; so whoever you are we’d love to get to know you.

Please be advised: Use of AI tools during interviews or assessments is strictly prohibited, unless otherwise instructed or agreed upon. We employ various methods to evaluate the authenticity of candidate responses.

Job Description

At Citadel Securities, a leading global market maker, our team of quantitative researchers models the markets and brings trading strategies to life every day. Specifically, this team develops and tests automated quant trading strategies using sophisticated statistical techniques. You'll get to challenge the impossible in quantitative research by applying sophisticated and complex statistical techniques to financial markets, some of the most complex data sets in the world.

As an intern, you'll dive into research through an 11 week program that will allow you to collaborate and connect with senior team members. In addition, you'll get the opportunity to network and socialize with peers throughout the internship.

Our signature internship program takes place June through August. Occasionally, we can be flexible to other times of the year. You will be able to indicate your timing preference in the application.

Your Objectives

• Conceptualize valuation strategies, develop and continuously improve upon mathematical models, and help translate algorithms into code
• Back test and implement trading models and signals in a live trading environment
• Use unconventional data sources to drive innovation
• Conduct research and statistical analysis to build and refine monetization systems for trading signals

Your Skills & Talents

• PhD degree in mathematics, statistics, physics, computer science, or another highly quantitative field
• Strong knowledge of probability and statistics (e.g., machine learning, time-series analysis, pattern recognition, NLP)
• Prior experience working in a data driven research environment
• Experience with translating mathematical models and algorithms into code (Python, R or C++)
• Independent research experience
• Ability to manage multiple tasks and thrive in a fast-paced team environment
• Excellent analytical skills, with strong attention to detail
• Strong written and verbal communication skills

Opportunities may be available from time to time in any location in which the business is based for suitable candidates. If you are interested in a career with Citadel Securities, please share your details and we will contact you if there is a vacancy available.

We collect and use personal data in accordance with our Privacy Policy. We retain data on prospective candidates and may consider suitability for alternative opportunities at Citadel Securities. For more information, see our Privacy Policy.

About Citadel Securities

Citadel Securities is a technology-driven, next-generation global market maker. We provide institutional and retail investors with world-class liquidity, competitive pricing and seamless front-to-back execution in a broad array of financial products. Our teams of engineers, traders and researchers harness leading-edge quantitative research and the accelerating power of compute, machine learning and AI to power our analytics and tackle the market’s and our clients’ most critical challenges. Together, we are forging the future of capital markets. For more information, visit citadelsecurities.com.

Job Description

Opportunities may be available from time to time in any location in which the business is based for suitable candidates. If you are interested in a career with Citadel, please share your details and we will contact you if there is a vacancy available.

Researchers build and deploy models across equities, options, fixed income, and derivatives domains, often working with petabyte-scale data.

Models incorporate advanced techniques: deep learning, sequence / time-series models, representation learning, and methods to tame overfitting and ensure robustness in financial regimes.

The goal: each model isn't a theoretical exercise — it has a measurable P&L impact (or reduces risk / cost) when deployed in live market-making or trading contexts.

Key Responsibilities:

• Conduct cutting-edge research and development in machine learning, with a focus on large language models (LLMs) and Deep learning and their applications in quantitative finance.
• Design, implement, and optimize machine learning models for performance and scalability, particularly in financial contexts.
• Collaborate with cross-functional teams to integrate ML solutions into business processes and trading strategies.

Skillset Requirements:

• Proficiency in creating and using algorithms to meticulously investigate and work through large data or error-checking problems
• Deep knowledge of LLM architectures, including transformers.
• Familiarity with attention mechanisms, normalization techniques, and model architecture design.
• Training techniques (pre-training, fine-tuning, RLHF), and optimization methods.
• Understanding of low-level details like GPU memory management, precision types (float16, bfloat16), and parallelization techniques.
• Proficiency in advanced training techniques such as pre-training, fine-tuning, RLHF, and DPO.
• Expertise in Python and ML frameworks like PyTorch or TensorFlow.
• Familiarity with Retrieval Augmented Generation (RAG) systems and their implementation.
• Proven ability to approach open-ended problems and design end-to-end solutions in ML/AI.
• Strong mathematical and statistical foundations, particularly in areas relevant to quantitative finance.

About Citadel Securities

Citadel Securities is a technology-driven, next-generation global market maker. We provide institutional and retail investors with world-class liquidity, competitive pricing and seamless front-to-back execution in a broad array of financial products. Our teams of engineers, traders and researchers harness leading-edge quantitative research and the accelerating power of compute, machine learning and AI to power our analytics and tackle the market’s and our clients’ most critical challenges. Together, we are forging the future of capital markets. For more information, visit citadelsecurities.com.

We have roles across 4 locations:

Beijing, China

London, UK

San Francisco, US

Sydney, AU

Vienna, Austria

About Canva

Canva's mission is to empower the world to design, with machine learning playing a central role. Our ML engineers work across product and platform teams, focusing on ranking and search systems, generative models, pipelines, and infrastructure that transform research breakthroughs into features for millions.

About the Role

As a Senior Machine Learning Engineer, you'll own scoped ML problems from start to finish: framing, building, evaluating, shipping, and measuring impact. Depending on your team, you might work on ranking models, generative pipelines, or transitioning research prototypes to production systems. You'll operate with high ownership and minimal guidance, collaborating closely with researchers, product engineers, and platform teams.

What You'll Do

• Build, evaluate, and deploy ML systems in production, handling ranking, relevance, generation, or evaluation infrastructure.
• Own projects from problem framing to measurable impact with minimal guidance.
• Balance production trade-offs like quality, cost, and latency in model integration.
• Investigate and resolve issues in live systems.
• Collaborate with research, product, and platform engineers to create actionable plans.
• Clearly communicate technical trade-offs and share knowledge across teams.

You're Likely a Match If You Have

• Experience deploying ML systems at scale, beyond just model training.
• Ability to define and impact key metrics, not just optimizing model accuracy.
• Proven track record of independently managing projects from idea to completion.
• Strong software engineering skills and proficiency in modern ML tools (e.g., Python, PyTorch).
• High autonomy and adaptability to evolving products and priorities.
• Excellent communication and collaboration skills.

Nice to Have

• Expertise in areas like search and ranking systems, generative model evaluation, distributed training, or MLOps.
• Experience with systems used by millions.
• A history of delivering ML-powered product features end to end.

At Canva, we value fairness, and we strive to provide competitive, market-informed compensation whilst ensuring internal equity within the team in each region. The target salary range for this position is $220,000 - $280,000. When calculating offers, we make salary decisions based on market data and candidates' skills and experience.

Job Description

About Global Quantitative Strategies (GQS)

Global Quantitative Strategies is the quantitative investment business of Citadel. Founded in 2012, GQS has rapidly grown into one of Citadel’s core investment strategies and one of the top quantitative investment teams in the world. Collaborative teams of researchers, engineers, and traders work together to develop robust systems and advanced quantitative models that allow us to operate at scale and identify investment opportunities across global markets.

Machine Learning Engineers (MLEs) in GQS work at the intersection of deep learning, quantitative research, and high-performance computing. In this role, you will collaborate closely with Quantitative Researchers and Quantitative Research Engineers to design, build, optimize, and scale the models and modeling systems that power research and production workflows.

This is not a traditional infrastructure engineering role. MLEs are deeply embedded in the research process, partnering with researchers to understand modeling challenges, translate research ideas into scalable model architectures, and improve the performance, reliability, and efficiency of machine learning systems. You will work on model architecture, distributed training, inference optimization, research tooling, and internal ML libraries that enable the development and deployment of models across major asset products globally. The work directly supports the research and productization of machine learning models used in systematic investing, including the development of new modeling approaches, the optimization of large-scale training workflows, and the creation of tools that help researchers experiment faster and more effectively.

Skills and Qualifications

• Bachelor’s, Master’s, or PhD degree in Computer Science, Engineering, Mathematics, Statistics, Machine Learning, or an equivalent technical field
• Strong programming skills in Python and experience with C++, CUDA, or other performance-oriented technologies
• Experience designing, implementing, training, or optimizing machine learning models, particularly deep learning models
• Strong understanding of model architecture, training dynamics, optimization techniques, and performance tradeoffs
• Experience working with PyTorch, TensorFlow, JAX, or similar machine learning frameworks
• Experience building or extending machine learning libraries, research tooling, model training systems, or distributed training workflows
• Ability to optimize ML workflows for training speed, inference performance, scalability, reliability, and cost efficiency
• Experience developing on a Linux stack and working in modern high-performance computing or distributed computing environments
• Ability to collaborate closely with researchers, understand open-ended research problems, and translate modeling needs into robust technical solutions
• Proven track record of solving complex technical problems with creativity, strong judgment, and attention to research impact
• Strong communication skills and the ability to work effectively across research, engineering, and infrastructure teams
• Interest in financial markets and applying machine learning to systematic investing

We collect and use personal data in accordance with our Privacy Policy. We retain data on prospective candidates and may consider suitability for alternative opportunities at Citadel. For more information, see our Privacy Policy.

In accordance with applicable law, the base salary range for this role is $275,000 to $350,000.

In addition, the employee who fills this role will be eligible to participate in a discretionary incentive compensation program, as well as a wide array of benefit programs, such as medical and life insurance, retirement and tax-free savings plans, and access to other healthcare programs.

About Citadel

Citadel is one of the world’s leading alternative investment managers. We manage capital on behalf of many of the world’