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.

Department of Computer Science, Stony Brook University Stony Brook, NY 11794

Postdoctoral Associate

Required Qualifications: (as evidenced by an attached resume) Doctoral Degree (or foreign equivalent) in Computer Science or a closely related field in hand by the appointment start date.

https://stonybrooku.taleo.net/careersection/2/jobdetail.ftl?job=2602791

Preferred Qualifications:
Research experience in computer vision, NLP, geospatial data systems, or high-performance computing.

Brief Description of Duties: The Postdoctoral Associate will assist the Principal Investigator Dr. Steven Skiena in the Department of Computer Science at Stony Brook University. The incumbent will conduct cutting-edge research at the intersection of AI/ML and extreme weather forecasting, employing data science models as developed in computer vision and natural language processing (NLP). This project leverages the large-scale high-performance computing (HPC) infrastructure of New York State’s Empire AI enabling us to train large AI models that will outperform traditional numerical prediction models.

Duties:

● Design, train, and evaluate novel AI/ML models. Develop computational innovations to enhance model efficiency, architecture, and performance.

● Collaborate on additional projects using text and vision models building on their own research interests.

● Co-author manuscripts for submission to leading scientific journals.

● Present research at group meetings, seminars, and conferences.

● Other duties as assigned.

Special Notes: The Research Foundation of SUNY is a private educational corporation. Employment is subject to the Research Foundation policies and procedures, sponsor guidelines and the availability of funding. FLSA Exempt position, not eligible for the overtime provisions of the FLSA. Minimum salary threshold must be met to maintain FLSA exemption.

Visit The Office of Postdoctoral Affairs to learn more about our postdoctoral community.

Resume/CV and cover letter should be included with the online application.

Stony Brook University is committed to excellence in diversity and the creation of an inclusive learning, and working environment. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sex, pregnancy, familial status, sexual orientation, gender identity or expression, age, disability, genetic information, veteran status and all other protected classes under federal or state laws.

If you need a disability-related accommodation, please call the university Office of Equity and Access (OEA) at (631) 632-6280 or visit OEA.

In accordance with the Title II Crime Awareness and Security Act a copy of our crime statistics can be viewed here.

Visit our WHY WORK HERE page to learn about the total rewards we offer.

SUNY Research Foundation: A Great Place to Work.

The starting salary range (or hiring range) to be offered for this position is noted below, it represents SBU’s good faith and reasonable estimate of the range of possible compensation at the time of posting.

We have roles across 4 locations:

Beijing, China

London, UK

San Francisco, US

Sydney, AU

Vienna, Austria

About the team

Canva Research aims to develop AI technology for Canva's Creative Operating System, enhancing design accessibility and innovation. Our team, established in June 2025, spans Sydney, London, Vienna, San Francisco, and Beijing. We focus on generative image, video, audio, agents, evaluations, on-device, and foundation models, turning research into user-friendly features.

About the role

As a Senior Research Scientist, you'll simplify advanced machine learning tools for Canva users, creating features that transform ideas into reality. Your role involves developing cutting-edge technologies to empower global design. We welcome diverse backgrounds in design, image/video generation, or LLM/RL. A strong foundation in generative modeling and quick adaptability to audio/video challenges are key.

Current focus

• Collaborating with Research Engineers on audio, video, and multimodal AI
• Leading research initiatives aligned with product and strategic goals
• Translating research insights into practical applications
• Tracking state-of-the-art technologies for integration
• Designing model architectures and algorithms for generative and multimodal content
• Optimizing models for efficiency in large systems
• Working with cross-functional teams to build impactful solutions

Ideal candidate

• Experience leading foundational or open model development in generative domains
• Proven research impact in academia or industry
• Deep understanding of AI models like Diffusion Models, GANs, Transformers, or large language models
• Expertise in adapting pre-trained models for enhanced control and quality
• Experience with large-scale AI models in image/video generation, audio, or LLM training
• Proficiency in Python, PyTorch, or Jax, and cloud platforms
• Strong communication, collaboration, and knowledge-sharing skills
• Curiosity and a keen interest in AI trends and technologies

Flow Traders is looking for a Senior Research Engineer to join our London office. This is a unique opportunity to join a leading proprietary trading firm with an entrepreneurial and innovative culture at the heart of its business. We value quick-witted, creative minds and challenge them to make full use of their capacities.

As a Senior Research Engineer, you will be responsible for helping to lead the development of our trading model research framework and using it to conduct research to develop models for trading in production. You'll expand the framework to become global standard way of training, consuming, combining, and transforming any data source in a data-driven systematic way. You will then partner with Quantitative Researchers to build the trading models themselves.

What You Will Do

• Help to lead the development and global rollout of our research framework for defining and training models through various optimization procedures (supervised learning, backtesting etc.), as well as its integration with our platform for deploying and running those models in production
• Partner with Quantitative Researchers to conduct research: test hypotheses and tune/develop data-driven systematic trading strategies and alpha signals

What You Need to Succeed

• Advanced degree (Master's or PhD) in Machine Learning, Statistics, Physics, Computer Science or similar
• 8+ years of hands-on experience MLOps, Research Engineering, or ML Research
• A strong background in mathematics and statistics
• Strong proficiency in programming languages such as Python, with experience in libraries like numpy, pytorch, polars, pandas, and ray
• Demonstrated experience in designing and implementing end-to-end machine learning pipelines, including data preprocessing, model training, deployment, and monitoring
• Understanding of and experience with modern software development practices and tools (e.g. Agile, version control, automated testing, CI/CD, observability)
• Understanding of cloud platforms (e. g., AWS, Azure, GCP) and containerization technologies (e. g., Docker, Kubernetes)

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

ADIA Lab, an independent research institution based in Abu Dhabi specializing in data and computational sciences, is seeking a Senior Computational Scientist with a focus on Material Sciences. This position plays a pivotal role in establishing a new research group, cultivating and expanding a globally recognized team of researchers, and leading lab-wide initiatives at ADIA Lab and within the broader international community. Our goal is to leverage computational science and data-driven discovery to accelerate breakthroughs in materials for energy, sustainability, and advanced technologies.

ADIA Lab is a global research center dedicated to advancing computational science, data science, and AI to address challenges in climate, health, digital economy, and materials science. Located in Abu Dhabi, the Lab brings together leading researchers from around the world to build foundational knowledge, develop innovative computational methods, and enable breakthroughs that have global impact.

Requirements Establish and lead a new Material Sciences research group within ADIA Lab, focusing on computational modeling, simulation, and data-driven materials discovery. Drive cross-disciplinary research combining physics-based modeling, data science, and high-performance computing to address grand challenges in materials for energy, climate, and technology. Develop and apply computational frameworks for multiscale modeling, quantum-to-continuum simulations, and AI-assisted materials design. Build and coordinate a strong, collaborative research team and network, with an emphasis on strategic leadership and partnership development. Collaborate with national and international research institutions, fostering a community science approach to accelerate progress in computational materials research. Build partnerships with universities, laboratories, and industry to initiate joint programs, funding proposals, and collaborative platforms for materials informatics and open data. Publish research results in high-impact journals, contribute to white papers and global assessments, and represent ADIA Lab at leading international conferences. Supervise and mentor junior scientists, postdoctoral fellows, and students, nurturing future leaders in computational materials science. Play a central role in shaping, growing, and coordinating the Materials Science group as a core pillar within ADIA Lab’s mission, ensuring long-term sustainability and global visibility. Work closely with ADIA Lab Fellows and the Advisory Board to shape the strategic direction of materials science research at ADIA Lab. Basic Requirements

PhD in materials science, physics, chemistry, computational science, applied mathematics, or a related field. Minimum of 6 years of post-PhD experience in computational materials research, data-driven materials design, or closely related domains. Preferred Qualifications

Proven record of leading a research group or major project in computational or data-driven materials science. Demonstrated expertise in atomistic and first-principles simulations (DFT, molecular dynamics), mesoscale modeling, or continuum methods. Experience with machine learning for materials discovery, data curation, and materials informatics platforms (e.g., Materials Project, NOMAD, AiiDA). Familiarity with high-performance computing environments, parallel programming, and workflow automation for large-scale simulations. Proficiency in programming languages such as Python, C/C++, Fortran, and tools including Git, Linux, and LaTeX. Strong publication record and recognized contributions to the international materials science community. Excellent leadership, mentoring, and communication skills.

Job Description

About Global Quantitative Strategies (GQS)

GQS is the quantitative investment business unit of Citadel. Founded in 2012, GQS has grown rapidly to become 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 build robust systems that operate at scale and apply advanced quantitative and machine learning techniques to identify investment opportunities.

Machine Learning Researchers at GQS develop and deploy models across a variety of asset classes. Their work spans deep learning, sequence and time-series modeling, natural language processing, large language models, pre-training, reinforcement learning, and methods for improving robustness in complex financial regimes.

Location

New York, Singapore

Required Skills and Qualifications:

• Advanced degree in Computer Science, Machine Learning, Mathematics, Statistics, Engineering, Physics, or a related quantitative field
• Proven ability to conduct innovative and impactful research focused on solving real-world problems
• Deep expertise in machine learning and deep learning, such as sequence modeling, large language models, or reinforcement learning
• Experience with modern training techniques such as pre-training, fine-tuning, reinforcement learning, or related optimization methods
• Expertise in Python and machine learning frameworks such as PyTorch or JAX
• Strong mathematical and statistical foundations
• Ability to design, implement, and optimize machine learning models for performance, scalability, and robustness
• Demonstrated interest in financial markets and a drive to apply machine learning techniques to model price formation, market behavior, and risk

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 $300,000 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’s preeminent private, public and nonprofit institutions. We seek the highest and best use of investor capital in order to deliver market leading results and contribute to broader economic growth. For over 30 years, Citadel has cultivated a culture of learning and collaboration among some of the most talented and accomplished investment professionals, researchers and engineers in the world. Our colleagues are empowered to test their ideas and develop commercial solutions that accelerate their growth and drive real impact.

We have roles across 4 locations:

Beijing, China

London, UK

San Francisco, US

Sydney, AU

Vienna, Austria

About the team

Canva Research's mission is to advance AI technology for Canva's Creative Operating System, making design accessible to everyone. Our team, established in June 2025, has rapidly grown across cities such as Sydney, London, Vienna, San Francisco, and Beijing. We focus on generative image, video, audio, agents, evaluations, on-device, and foundation models, transforming research breakthroughs into features that enhance Canva's platform.

About the role

As a Senior Research Engineer, you will be integral in transforming Canva Research's innovations into scalable products. Your role involves taking research prototypes in areas like generative models and agents, and developing them into technology that millions use for creative storytelling. We welcome candidates from various backgrounds, including generative model engineering, agent systems, evaluation infrastructure, or systems optimization. The key requirement is strong production ML engineering skills and the ability to judge when a product is ready to ship.

What you'll do

• Design systems to convert generative research into features, such as model serving and on-device deployment
• Evaluate systems for model selection and measure effectiveness
• Manage infrastructure for large-scale training, evaluation, and deployment
• Develop evaluations capturing real quality and user intent
• Collaborate with product teams to integrate research prototypes into Canva features
• Enhance and scale models for efficiency across distributed systems
• Work with cross-functional teams to create impactful solutions

You're likely a match if you have

• 5+ years of ML research or engineering experience with a proven track record in production
• Strong software engineering skills in Python for building scalable ML systems
• Hands-on experience in generative model training, agent architectures, or systems optimization
• Familiarity with large-scale distributed training and serving infrastructure
• Strong experimental skills and ability to translate research into scalable systems
• Excellent communication skills and ability to work collaboratively with research scientists
• Curiosity and awareness of industry trends and emerging technologies

Nice to have

• Knowledge of multimodal data or models
• Experience in designing evaluations for ML products
• Open-source contributions or publications in ML systems or multimodal research
• Experience with creative tools or design tooling

INTERNSHIP OPPORTUNITY The Data Science Intern(s) will work closely with other members of the Data Science team, Investment Analysts, and Data Engineers to analyze, extend, and build on Viking’s significant repository of alternative data assets and generate actionable investment insights.

We seek an analytical and creative problem solver and provide them with the resources and tools to apply their Data Science training and experience to our most pressing and interesting research questions. The Data Science Intern will both work independently and collaborate with other intellectually curious quantitative professionals. This is a 10-week internship taking place over the summer.

Informational webinar: October 21, 6:00-7:00pm ET. Register here: https://vikingglobal.zoom.us/webinar/register/WN_0JZYSHQZSai4xco76Q5O3A

RESPONSIBILITIES Data Science Intern(s) will have the opportunity to develop impactful analyses and insights to be used across our investment process and organization. Activities could include but are not limited to: Build and deliver predictive analytics on companies, sectors, and macroeconomic trends Translate alternative data analysis into actionable insights for the investment team Develop methodologies to identify and evaluate investment opportunities in private companies Identify and evaluate new data sources Streamline the data life cycle, operating model, and process Test and evaluate new technologies to enhance our big data platform Create centralized and automated analyses and processes Contribute to Viking’s overall research effort by sharing information and insights across the firm

QUALIFICATIONS Across the firm, we attract motivated, intellectually curious, and analytically rigorous people who are passionate about learning and creating impact. The ideal candidate will possess the following traits: A strong performer currently pursuing a Master’s degree or a PhD program (3rd year and above) in Data Science, Economics, Finance, Statistics, Operations Research, or related quantitative fields Strong communication skills, with the ability to convey complex ideas to a non-technical audience Independence of thought and ability to carry out a research project with partial supervision Proficiency in Python and statistical libraries, and working knowledge of SQL, BI software (e.g., Tableau), cloud technologies, and modern LLM tooling (Claude Code, Codex, etc.) Sound judgment and ability to take a step back from the analysis and look at the big picture Passion for research, proactive and self-motivated Commitment to excellence

APPLICATION: Please submit your resume / application through the Viking career site via this link: Please remember to indicate your school name on the application page. Please merge your resume and brief research supplement into a single PDF file (resume first, supplement second) before submitting. Applications missing either component will not be reviewed. In 1-2 pages, the supplement should describe a quantitative research project that you recently completed. Please include: The research question you were trying to answer The data you used Your approach, including details on the statistical methodologies Your findings The computational environment (e.g., language, main libraries, etc.) Please note our application deadline is November 10, 2026 (11:59PM EST). Incomplete applications will not be considered. Interview process: Our interviews will take place virtually in December/January.

The base salary range for this position in New York City is annual $175,000 to $250,000. In addition to base salary, Viking employees may be eligible for other forms of compensation and benefits, such as a discretionary bonus,100% coverage of medical and dental premiums, and paid lunches. Actual compensation for successful candidates will be individually determined based on multiple factors including, but not limited to, a candidate’s skill set, experience, education, and other qualifications.

The Team

Our AI research team sits at the heart of our mission to unlock new dimensions of biological understanding. You will leverage state-of-the-art AI to accelerate discovery and drive transformative insights in biology—developing novel AI models purpose-built for biological research, engineering robust systems that enable breakthrough science at unprecedented scale, and translating these advances into practical tools that empower researchers worldwide. Our approach is comprehensive and integrated, bringing together world-class AI model development, exceptional engineering talent, high-quality biological data, powerful computing infrastructure, and strategic partnerships. Success requires excellence across five interconnected pillars: training frontier AI models specifically for biology; building engineering systems that maximize research velocity and efficiency; executing a sophisticated data strategy that fuels AI development; operating a world-class AI compute platform; and creating impactful products that transform AI capabilities into accessible scientific tools.

The Opportunity

This role is part of the Data team, which focuses on owning the strategy, sourcing and implementation for data supporting AI research and development. Our goal is to maximize the speed, agility, and capability of biological AI research by connecting public data resources and Biohub's experimental platforms to AI systems. The data that trains biological frontier models comes in dozens of modalities—sequences, images, spatial coordinates, time series, molecular structures, metadata, preprints and published papers—each with its own noise characteristics, biases, and information content. The question of how to represent this data for learning is one of the most important open problems in biological AI.

What You'll Do

Design data representations and tokenization strategies for imaging data that enable novel model architectures Coordinate Experimental, Data Science, Data Engineering and AI Research teams to translate biological structure into learnable representations—defining priorities and appropriate structures for metadata and data that information models can access and consume Work across those teams to guide data acquisition priorities, define quality criteria, and assess external datasets from a representation perspective Develop and validate approaches for combining heterogeneous data modalities into unified training frameworks, designing for robustness to noise, bias, and batch effects Evaluate how representation choices impact model performance, identifying which biological signals are captured or lost and iterating to improve

What You'll Bring

PhD in computational biology, bioinformatics, or a quantitative biological field Experience with tokenization strategies for non-text data (images, sequences, graphs, time series) Track record of novel methodological contributions (publications, open-source tools, or production systems) Familiarity with biological foundation models (ESM, scGPT, or similar) Deep understanding of imaging data, their underlying data characteristics, and how to transform raw data into ai-ready datasets. Experience designing data representations or feature engineering for machine learning, ideally in scientific or biological contexts Familiarity with modern ML architectures (transformers, diffusion models, or similar) and how data representation choices affect learning Strong computational skills (Python, scientific computing libraries); comfort working with large-scale datasets Creative, first-principles thinking about how to structure data for learning

Compensation The Redwood City, CA base pay range for a new hire in this role is $214,000 - $294,800. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.