NeurIPS 2025 Career Opportunities

Johns Hopkins University

We invite applications for Postdoctoral Fellow positions in the broad areas of data science and AI, with a focus on developing and applying novel data science approaches, computational tools and statistical methods to advance health and biomedical research. Johns Hopkins University has recently made transformative new investment in launching a new Data Science and AI institute that will serve as the hub for interdisciplinary data collaborations with faculties and students from across Johns Hopkins and will build the nation’s foremost destination for emerging applications, opportunities and challenges presented by data science, machine learning and AI.

San Francisco / New York / Toronto

About Ideogram

Ideogram’s mission is to make world-class design accessible to everyone, multiplying human creativity. We build proprietary generative media models and AI native creative workflows, tackling unsolved challenges in graphic design. Our team includes builders with a track record of technology breakthroughs including early research in Diffusion Models, Google’s Imagen, and Imagen Video. We care about design, taste, and craft as much as research and engineering – shipping experiences that creatives actually love.

We’ve raised nearly $100M, led by Andreessen Horowitz and Index Ventures. Headquartered in Toronto with a growing team in NYC, we're scaling fast, aiming to triple over the next year. We're a flat team with a culture of high ownership, collaboration, and mentorship.

Explore Ideogram 3.0, Canvas, and Character blog posts, and try Ideogram at ideogram.ai.

The Opportunity

In this role, you will develop the post-training pipeline for our text-to-image foundation models end to end, from data strategy to deployment, advancing techniques such as RLHF, RLAIF, and work on personalization/customization. You will contribute to post-training research that drives measurable gains, and implement and maintain high-throughput fine-tune/eval pipelines. You'll work with a creative and ambitious team of engineers and researchers who are building the future of the creative economy.

What We're Looking For

• 5+ years of experience in developing machine learning models in JAX, PyTorch, or TensorFlow.

• Experience in implementing Machine Learning foundations (e.g., Transformer, VAE, Denoising Diffusion models) from scratch.

• Track record in machine learning innovation and familiarity with Deep Learning and advanced Machine Learning.

• End-to-end understanding of generative media applications and excitement for pushing the state-of-the-art in generative AI.

• Ability to debug machine learning models to iteratively improve model quality and performance.

• Nice to have: Familiarity with Kubernetes and docker.

• Optional: Experience in low-level machine learning optimization, e.g., writing CUDA kernel code.

Our Culture

We’re a team of exceptionally talented, curious builders who love solving tough problems and turning bold ideas into reality. We move fast, collaborate deeply, and operate without unnecessary hierarchy, because we believe the best ideas can come from anyone.

Everyone at Ideogram rolls up their sleeves to make our products and our customers successful. We thrive on curiosity, creativity, and shared ownership. We believe that small, dedicated teams working together with trust and purpose can move faster, think bigger, and create amazing things.

Ideogram is committed to welcoming everyone — regardless of gender identity, orientation, or expression. Our mission is to create belonging and remove barriers so everyone can create boldly.

What We Offer

💸Competitive compensation and equity designed to recognize the value and impact of your contributions to Ideogram’s success. 🌴 4 weeks of vacation to recharge and explore. 🩺 Comprehensive health, vision, and dental coverage starting on day one. 💰 RRSP/401(k) with employer match up to 4% to invest in your future from the moment you join. 💻 Top-of-the-line tools and tech to fuel your creativity and productivity. 🔍 Autonomy to explore and experiment — whether you’re testing new ideas, running large-scale experiments, or diving into research, you’ll have access to compute/resources you need when there’s a clear business or creative use case. We encourage curiosity and bold thinking. 🌱 A culture of learning and growth, where curiosity is encouraged and mentorship is part of the journey. 🏡 Fully remote flexibility across North America, with regular in-person team meetups and collaboration opportunities.

Global

Description

Qualcomm is proud to be attending NeurIPS 2025 in our home city San Diego, California! Qualcomm is powering efficient AI from edge to cloud, conducting novel foundational, platform, and applied AI research to enable intelligent computing everywhere.

We're inviting all those who have a passion for AI and are interested in opportunities in generative AI, visual AI, computer vision, and foundational machine learning to please follow the steps below.

1. Go to our Qualcomm - NeurIPS home page.

2 .Register by clicking on the blue link. This allows us to identify your application as someone we met at NeurIPS.

1. Apply to any of the linked positions below. Make sure you REGISTER first before applying. Your resume will stand out.

London

Flow Traders is looking for a Senior Research Engineer to join our Hong Kong 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)

Who we are:

Peripheral is developing spatial intelligence, starting in live sports and entertainment. Our models generate interactive, photorealistic 3D reconstructions of sporting events, building the future of live media. We’re solving key research challenges in 3D computer vision, creating the foundations for the next generation of robotic perception and embodied intelligence.

We’re backed by Tier-1 investors and working with some of the biggest names in sports. Our team includes top robotics and machine learning researchers from the University of Toronto, advised by Dr. Steven Waslander and Dr. Igor Gilitshenski.

Our team is ambitious and looking to win. We’re seeking a Machine Learning engineer to develop our motion capture models through synthetic data curation, model training, and inference-time optimization.

What you’ll be doing:

• Developing our data flywheel to autolabel and generate synthetic data,

• Improving our motion capture accuracy by fine-tuning existing models on our domain,

• Optimizing inference time through model distillation and quantization,

What we’d want to see:

• Prior experience with 3D computer vision and training new ML models,

• Strong understanding of GPU optimization methods (Profiling, Quantization, Model Distillation),

• Proficiency in Python and real-time ML inference backends,

Ways to stand out from the crowd:

• Previous experience in architecting and optimizing 3D computer vision systems,

• Strong understanding of CUDA and Kernel programming,

• Familiarity with state-of-the-art research in VLMs,

• Top publications at conferences like NeurIPS, ICLR, ICML, CVPR, WACV, CoRL, ICRA,

Why join us:

• Competitive equity as an early team member.

• $80-120K CAD + bonuses, flexible based on experience.

• Exclusive access to the world’s biggest sporting events and venues,

• Work on impactful projects, developing the future of 3D media and spatial intelligence.

To explore additional roles, please visit: www.peripheral.so

Location: Toronto, ON, Canada

Bala Cynwyd (Philadelphia Area), Pennsylvania United States & New York, New York United States

Overview

Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.

As a Machine Learning Intern at Susquehanna, you’ll work on high-impact projects that closely reflect the challenges and workflows of our full-time research team. You’ll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna’s research and trading systems. You will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.

What You Can Expect

 • Conduct research and develop ML models to identify patterns in noisy, non-stationary data

 • Work side-by-side with our Machine Learning team on real, impactful problems in quantitative trading and finance, bridging the gap between cutting-edge ML research and practical implementation

 • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches

 • Design and run experiments using the latest ML tools and frameworks

 • One-on-one mentorship from experienced researchers and technologists

 • Participate in a comprehensive education program with deep dives into Susquehanna’s ML, quant, and trading practices

 • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior

 • Explore various aspects of machine learning in quantitative finance from alpha generation and signal processing to model deployment and risk-aware decision making

What we're looking for

 • Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field

 • Proven experience applying machine learning techniques in a professional or academic setting

 • Strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR

 • Hands-on experience with machine learning frameworks, including PyTorch and TensorFlow

 • Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment

Why Join Us?

 • Work with a world-class team of researchers and technologists

 • Access to unparalleled financial data and computing resources

 • Opportunity to make a direct impact on trading performance

 • Collaborative, intellectually stimulating environment with global reach

The Chan Zuckerberg Biohub Network (https://www.czbiohub.org/) is a group of nonprofit research institutes that bring together scientists, engineers, and physicians with the goal of pursuing grand scientific challenges on 10- to 15-year time horizons. The CZ Biohub Network focuses on understanding underlying mechanisms of disease and developing new technologies that will lead to actionable diagnostics and effective therapies.

We pursue large scientific challenges that cannot be pursued in conventional environments We enable individual investigators to pursue their riskiest and most innovative ideas The technologies developed at the CZ Biohub Network facilitate research by scientists and clinicians at our home institutions and beyond Diversity of thought, ideas, and perspectives are at the heart of CZ Biohub Network and enable disruptive innovation and scholarly excellence. We are committed to cultivating an organization where all colleagues feel inspired and know their work makes an important contribution.

The Biohub Network is seeking an accomplished computational biologist and machine learning/AI specialist to join our interdisciplinary team. This role requires experience in research settings, a background in biology, and a proven ability to design, evaluate, and publish innovative computational methodologies that leverage machine learning, statistics, language modelling, and AI to advance biological research and discovery. Research projects to accelerate the rate of scientific discovery will be assigned by the President of the New York location, and in collaboration with research teams across the organization.

The ideal candidate will have a strong track record of accomplishments and a dedication to collaborative work within a highly interdisciplinary environment.

This role is based out of the New York location.

What You'll Do - Contribute to a dynamic, innovative, and collaborative program that aligns with the mission of CZ Biohub NY. - Develop and evaluate cutting-edge computational / AI methodologies using data generated from across all research groups and incorporating relevant available datasets for to develop predictive models. - Collaborate within an interdisciplinary research environment to develop, test, and validate models. - Engage with colleagues throughout the Biohub to uphold our values of scholarly excellence, innovation, open communication, hands-on hacking, and partnership. - Communicate progress and results with colleagues inside and outside of your team. - Publish and disseminate impactful findings through preprints (medRxiv, bioRxiv) and/or software repositories (e.g., GitHub). - Work with the CZ Biohub team to patent and license technologies resulting from your research.

What You'll Bring - PhD in Computational Biology, AI / Machine learning, Applied Statistics or a MS plus relevant job experience. - Background in relevant areas of biomedical science, demonstrating a deep understanding of cellular biology, transcription and protein signal transduction. - 2-4 years of post-doctoral and/or industry experience demonstrating the ability to implement, evaluate, and create new computational methodologies that leverage machine learning, statistics, and AI for biological research and discovery. - Experience in building and evaluating machine learning and/or neural network models on biological data, with a deep understanding of feature selection, regularization, model introspection, and interpretability. - Proficiency in using and modifying probabilistic learning or deep learning models such as RNNs, GNNs, protein sequence models, or natural language processing models. - Proven track record of individual innovation, as well as a strong ability to work collaboratively. - Outstanding interpersonal and communication skills. - Demonstrated commitment to open science and alignment with the mission and values of CZ Biohub.

London

Description - Bloomberg’s Engineering AI department has 350+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products.

At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.

Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions. Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.

We are looking for Senior AI Engineers with expertise and a passion for Information Retrieval, Search technologies, Natural Language Processing and Generative AI to join our AI Experiences team. Our teams are working on exciting initiatives such as:

-Developing and deploying robust Retrieval-Augmented Generation (RAG) systems, curating high-quality data for model training and evaluation, and building evaluation frameworks to enable rapid iteration and continuous improvement based on real-world user interactions. -Designing and implementing tools that enable LLM-powered search agents to effectively handle complex client queries, shaping Bloomberg's generative AI ecosystem, and scaling these innovative solutions to support thousands of users. -Leveraging both traditional ML approaches and Generative AI to prototype, build, and maintain high-performing, client-facing search and streaming applications that deliver timely and relevant financial insights. -Building robust APIs to facilitate search across diverse collections of data, ensuring highly relevant results and maintaining system stability and reliability.

You'll have the opportunity to: -Collaborate closely with cross-functional teams, including product managers and engineers, to integrate AI solutions into client facing products , enhance analytical capabilities and improve user experience. -Architect, develop, and deploy production-quality search systems powered by LLMs, emphasizing both ML innovation and solid software engineering practices. -Continuously identify areas for improvement within our search systems, proactively experiment with new ideas, and rapidly implement promising solutions—even when improvements rely purely on engineering without direct ML involvement. -Design, train, test, and iterate on models and algorithms while taking ownership of the entire lifecycle, from idea inception to robust deployment and operationalization. -Stay at the forefront of research in IR, NLP, and Generative AI, incorporating relevant innovations into practical, impactful solutions. -Represent Bloomberg at industry events, scientific conferences, and within open-source communities.

USA - Seattle

Job Overview

At Arm, our research shapes the future of energy-efficient AI. We build the foundations of tomorrow’s intelligent systems - from next-generation processors and accelerators to cutting-edge ML models and tools. As Research Scientist, you’ll be part of a global team pushing the boundaries of what’s possible at the intersection of AI, architecture, and scalable compute.

We’re looking for curious, collaborative researchers who want to turn deep technical insights into real-world impact. Whether you’re advancing algorithms for efficient learning, designing ML-friendly compute architectures, or experimenting with new model deployment paradigms - your work at Arm can influence billions of devices worldwide.

Responsibilities

Your contributions will vary depending on your expertise, but may include: Investigating novel approaches and applications in machine learning Exploring how to make machine learning models and workloads more scalable, portable, and power-efficient Developing proof-of-concepts, prototypes, or simulation environments to test research ideas Collaborating with teams across Arm to integrate research into products and platforms Publishing, presenting, or contributing to academic and industrial research communities Working with partners and ecosystem stakeholders on long-term innovation initiatives

Required Skills and Experience

Strong foundational experience in machine learning, computer science, electrical / computer engineering, or related field. Proficiency in programming languages such as Python, C/C++, or similar Experience designing, training, or analyzing machine learning models or systems Interest in research and long-term innovation beyond immediate product delivery

“Nice to Have” Skills and Experience

Up to date understanding of machine learning trends Contributions to open-source or peer-reviewed publications Exposure to deploying machine learning models on edge, devices, or mobile platforms Familiarity with machine learning model optimization or deployment Familiarity with Arm architecture

New. York, NY

Applications are invited for postdoctoral Flatiron Research Fellowships (FRFs) at the Center for Computational Mathematics (CCM) in the Flatiron Institute. FRF positions are initially two-year appointments, renewable for a third year contingent on performance. Fellows will be based, and have a principal office or workspace, at the Simons Foundation’s offices in New York City. Fellows may also be eligible for subsidized housing within walking distance of the Flatiron Institute. The start date is between July and October 2026.

To apply and for more details: https://apply.interfolio.com/173401