Shanghai

Key Responsibilities • Building the compute platform and machine learning libraries for large scale machine learning and simulation workloads • Focus on compute platform stability and efficiency on both CPU and GPU clusters, making the platform observable and scalable • Utilize cluster monitoring and profiling tools to identify bottlenecks and optimize both infrastructure and software system • Troubleshoot and resolve issues related to OS, storage, network, and GPUs

Challenges You Will Tackle: design, build and improve our compute platform for PB scale data model training and simulations with a wide range of machine learning models by leveraging our existing research infrastructure.

Requirements: • Solid experience in running production machine learning infrastructure at a large scale • Experience in designing, deploying, profiling and troubleshooting in Linux-based computing environments • Proficiency in containerization, parallel computing and distributed training algorithms • Experience with storage solutions for large scale, cluster-based data intensive workloads

Bonus qualification: • Experience of supporting machine learning researchers or data scientists for production workloads

WHAT YOU CAN EXPECT FROM US: In return for you joining our elite team, you will be offered a competitive salary package as well as access to a plethora of Optiver-perks. To hear more about what it is like to work here and our great culture, apply now and take the first step towards the best career move you will ever make!

DIVERSITY AND INCLUSION Optiver is committed to diversity and inclusion, and it is hardwired through every stage of our hiring process. We encourage applications from candidates from any and all backgrounds, and we welcome requests for reasonable adjustments during the process to ensure that you can best demonstrate your abilities.

PRIVACY DISCLAIMER

Optiver 重视个人信息的保护。请您在提供个人信息给我们之前，认真阅读Optiver China Privacy Notice, 了解我们如何收集及处理您的个人信息。 Personal information protection is of utmost importance to Optiver. Before you provide any personal information to us, we strongly urge you to read our Privacy Policy to acknowledge how we collect and process your personal information.

Pinely is a privately owned algorithmic trading firm specializing in high-frequency and mid-frequency trading. We’re based in Amsterdam, Cyprus, and Singapore, and we’re experiencing rapid growth. We are looking for a DL Research Group Lead to drive cutting-edge AI research and lead a core DL subgroup. As DL becomes a central engine of the business, your team’s impact will grow across major markets and asset classes.

Responsibilities:

• Lead development of AI models, especially foundational models for market data, to predict prices in noisy, fast-changing markets;
• Set the research agenda, design experiments, and validate results;
• Build and manage a high-performing research team;
• Ensure a fast, transparent, value-driven research process;
• Integrate contributions from multiple researchers into production-ready solutions;
• Contribute hands-on to coding and strategy development;
• Expand responsibilities within the DL department over time.

Requirements:

• Strong DL researcher with technical leadership experience;
• Preferably experienced in high-end AI domains (LLMs, reasoning, generative models);
• Motivated by deep research and real-world impact;
• Able to maintain high pace while supporting a healthy team culture;
• Trading experience optional — first-principles thinking is key.

What we offer:

• Relocation package to Amsterdam
• High impact on a core business function and direct influence on real PnL;
• Minimal bureaucracy, fast feedback loops, massive datasets, reproducible experiments;
• Strong engineering support and an H200-based Data Center growing 2× yearly;
• Work on extremely challenging, non-stationary markets with low signal-to-noise;
• Opportunity to build foundational models for finance and shape the future of quant AI;
• Freedom to pursue deep research and define your modeling vision;
• A top-tier team, on-site in Amsterdam, working directly with founders;
• Influence over team hiring and development.
• Internal training, comprehensive health insurance, sports reimbursement, and biannual corporate events

The Deep Learning for Precision Health Lab (www.montillolab.org ), a part of the Biodata Engineering Program of the Biomedical Engineering Department at the University of Texas Southwestern in Dallas, TX seeks a talented and motivated Computational Research Scientist to support large-scale multimodal neuroimaging and biomedical data analysis initiatives and to support advanced AI. The successful candidate will play a key role in curating and analyzing multimodal datasets, preparing resources for foundation model development, and supporting NIH-funded projects at the intersection of machine learning, medical image analysis, neuroscience, and oncology. This is a full-time, long-term staff scientist position focused on technical excellence, reproducible data management, and collaborative research in a dynamic academic environment. The successful candidate’s work will directly inform AI-driven discovery in neurological and oncologic diseases.

With cutting-edge computational infrastructure, access to leading neurology, neuroscience, and cancer experts, and an unparalleled trove of high-dimensional imaging and multi-omic data, our machine learning lab is poised for success in these research endeavors.

Primary Responsibilities

• Configure/develop and run existing foundation or large-scale deep learning models for benchmarking.
• Contribute to manuscript writing and code documentation.
• Curate and manage large neuroimaging & bioimaging datasets that include structural, diffusion, and functional MRI, dynamic PET, EEG, fluorescence microscopy, and multi-omic or clinical data drawn from NIH-supported consortia.
• Develop and maintain automated pipelines for data quality control and reproducibility.
• Clean and prepare datasets for downstream ML and deep-learning workflows.

Qualifications

• M.S. or Ph.D. in Computer Science, Biomedical Engineering, Electrical Engineering, Physics, Statistics, or a closely related computational field.
• Candidates must have extensive neuroimaging and biomedical image analysis experience.
• Candidates must have existing mastery of one or more mainstream DL frameworks (e.g., PyTorch, TensorFlow) and be able to explain intricacies of the DL models they have constructed.
• Experience running and managing batch jobs on SLURM or similar HPC systems.
• Preferred: familiarity with neuroimaging data formats (DICOM, NIfTI, HDF5, MP4, EEG) and web-scraping or data-discovery scripting.

Compensation and Appointment

• Term and Location: Full-time, On-site in Dallas, TX (5 days/week)
• Salary: Highly competitive and commensurate with experience.
• Work Authorization: Must be legally authorized to work in the U.S.
• Mentorship: Direct supervision by Dr. Albert Montillo with opportunities for co-authorship and professional growth in mentoring junior team members and leading publications.

For consideration:

Reach out for an in-person meeting in San Diego at NeurIPS 2025 (or virtually afterwards) via email to Albert.Montillo@UTSouthwestern.edu with the subject “ComputationalResearchScientist-Applicant-NeurIPS” and include: (1) CV, (2) contact information for 3 references, (3) up to three representative publications, and (4) your start window. Positions are open until filled; review begins immediately.

Looking to study for a PhD?

I am looking for new students to join my ML group at the University of New South Wales, Sydney, Australia. The UNSW is ranked #19 in the QS Ranking 2025.

1. To succeed, you need an outstanding publication record, e.g., one or more first-author papers in NeurIPS, ICML, ICLR, CVPR, AAAI, ICCV, ECCV, IJCAI, SIG KDD, etc. You also need a high GPA from a very good uni (high in rankings). Patents, professional experience and non-first authors in the mix also help.

2. Topics include (non-exhaustively): (provable) machine UNlearning and model adaptation, MMLM and improving modality alignment, super-alignment, self-supervised physics-grounded models, safety in ML protein representations (also safety in general models), structured/technical diagrams understanding, structural diffusion models, next gen architectures beyond transformers, billion nodes/edges large scale graph learning.

3. Opportunities: CSC scholarships (due 16 Jan 2026) with uni. top-up, international scholarship rounds (due 17 April 2026), for exceptional candidates direct funding may be available (flex start)

Contact: Assoc. Prof. Piotr Koniusz: p.koniusz@unsw.edu.au See: www.koniusz.com (if you are attending NeurIPS, you can try reach me for an informal chat)

New York

As a Data Scientist, you will analyze complex datasets, build predictive models, and generate insights that drive strategic decisions. You’ll partner with engineers, researchers, and business leaders to turn data into actionable outcomes. 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.

Hong Kong

Flow Traders is committed to leveraging the most recent advances in machine learning, computer science, and AI to generate value in the financial markets. We are looking for Quantitative Researchers to join this challenge.

As a Quantitative Researcher at Flow Traders, you are an expert in mathematics and statistics. You are passionate about translating challenging problems into equations and models, and have the ability to optimize them using cutting-edge computational techniques. You collaborate with a global team of researchers and engineers to design, build, and optimize our next generation of models and trading strategies.

Are you at the top of your quantitative, modeling, and coding game, and excited by the prospect of demonstrating these skills in competitive live markets? Then this opportunity is for you.

AI Platform Engineer

Location: Boston (US) / Barcelona (Spain)

Position Overview

As an AI Platform Engineer, you are the bridge between AI research and production software. You will:

• Build and maintain AI infrastructure: model serving, vector databases, embedding pipelines
• Enable AI developers to deploy their work reproducibly and safely
• Design APIs for AI inference, prompt management, and evaluation
• Implement MLOps pipelines: versioning, monitoring, logging, experimentation tracking
• Optimize performance: latency, cost, throughput, reliability
• Collaborate with backend engineers to integrate AI capabilities into the product

Key Responsibilities

AI Infrastructure

• Deploy and serve LLMs (OpenAI, Anthropic, HuggingFace, fine-tuned models)
• Optimize inference latency and costs
• Implement caching, rate limiting, and retry strategies

MLOps & Pipelines

• Version models, prompts, datasets, and evaluation results
• Implement experiment tracking (Weights & Biases)
• Build CI/CD pipelines for model deployment
• Monitor model performance and drift
• Set up logging and observability for AI services

API Development

• Design and implement APIs (FastAPI)
• Create endpoints for prompt testing, model selection, and evaluation
• Integrate AI services with backend application
• Ensure API reliability, security, and performance

Collaboration & Enablement

• Work with AI Developers to productionize their experiments regarding improving user workflows
• Define workflows: notebook/test repository → PR → staging → production
• Document AI infrastructure and best practices
• Review code and mentor AI developers on software practices

Required Skills & Experience

Must-Have

• 7+ years of software engineering experience (Python preferred)
• Experience with LLMs and AI/ML in production: OpenAI API, HuggingFace, LangChain, or similar
• Understanding of vector databases (Pinecone, Chroma, Weaviate, FAISS)
• Cloud infrastructure experience: GCP (Vertex AI preferred) or AWS (SageMaker)
• API development: FastAPI, REST, async programming
• CI/CD and DevOps: Docker, Terraform, GitHub Actions
• Monitoring and observability
• Problem-solving mindset: comfortable debugging complex distributed systems
• Operating experience with AI deployment in enterprise environment

Nice-to-Have

• Experience fine-tuning or training models
• Familiarity with LangChain, Pydantic AI or similar frameworks
• Knowledge of prompt engineering and evaluation techniques
• Experience with real-time inference and streaming responses
• Background in data engineering or ML engineering
• Understanding of RAG architectures
• Contributions to open-source AI/ML projects

Tech Stack

Current Stack:

• Languages: Python (primary), Bash
• AI/ML: OpenAI API, Anthropic, HuggingFace, LangChain, Pydantic AI
• Vector DBs: Pinecone, Chroma, Weaviate, or FAISS
• Backend: FastAPI, SQLAlchemy, Pydantic
• Cloud: GCP (Vertex AI, Cloud Run), Terraform
• CI/CD: GitHub Actions
• Experiment Tracking: MLflow, Weights & Biases, or custom
• Containers: Docker, Kubernetes (optional)

What we offer:

Competitive compensation

Stock Options Plan: Empowering you to share in our success and growth.
Cutting-Edge Tools: Access to state-of-the-art tools and collaborative opportunities with leading experts in artificial intelligence, physics, hardware and electronic design automation.
Work-Life Balance: Flexible work arrangements in one of our offices with potential options for remote work.
Professional Growth: Opportunities to attend industry conferences, present research findings, and engage with the global AI research community.
Impact-Driven Culture: Join a passionate team focused on solving some of the most challenging problems at the intersection of AI and hardware.

Senior Research Fellow

Job Reference: 521361
Employment Type: Full Time (Fixed Term, 2 Years)
Location: Perth, Western Australia

Remuneration

Base salary: Level C, $144,143–$165,809 p.a. (pro-rata) plus 17% superannuation

The Research Centre

The Planning and Transport Research Centre (PATREC) at UWA conducts research with direct application to transport planning and road safety. RoadSense Analytics (RSA) is a video analytics platform for traffic analysis, developed through seven years of sustained R&D. The platform translates Australian research into a market-ready product for transport planning applications.

The Role

You will lead advanced research and development of computer vision and AI/ML models for traffic video analytics, focusing on detection, tracking, trajectory analysis, and robustness in complex conditions. You will conduct large-scale benchmarking, optimisation, and deployment of AI models, ensuring research innovations translate into real-world applications within the RoadSense Analytics platform. You will mentor junior researchers, collaborate with engineers, and contribute to knowledge building while pioneering state-of-the-art methods in multi-object tracking, trajectory reconstruction, and error reduction.

Selection Criteria

Essential:

• Tertiary degree in Computer Science, Applied Mathematics/Statistics, Robotics, Physics, or related discipline, with excellent academic record
• Demonstrated expertise and leadership in computer vision and machine learning research, including object detection, multi-object tracking, and segmentation
• Evidence of leading research projects, teams, or collaborations, with measurable outcomes
• Strong record of publications or equivalent applied research outputs in AI/ML or computer vision
• Experience translating AI/ML research into real-world applications or systems

Further Information

Position Description: PD [Senior Research Fellow] [521361].pdf

Contact: Associate Professor Chao Sun
Email: chao.sun@uwa.edu.au

Successful candidates will contribute to building and deploying AI-powered systems, including automated code generation, smart agents, retrieval-augmented generation (RAG) frameworks, and tools that integrate cutting-edge AI with scientific software and machine learning research. These systems aim to support drug discovery programs, increase research productivity, and improve the quality and efficiency of ML model training through intelligent data workflows and feedback loops. Candidates should have a strong interest in artificial intelligence (specifically, generative and agentic AI), with responsibilities spanning end-to-end system design: from idea conception and rapid prototyping to production-scale deployment. They should be comfortable working in a fast-paced environment where innovation, experimentation, and rigorous software engineering are all valued, but specific knowledge of any of these areas is less critical than intellectual curiosity, versatility, and a track record of achievement and innovation in the field of AI. For more information, visit www.DEShawResearch.com.

Please apply using this link:

https://apply.deshawresearch.com/careers/Register?pipelineId=923&source=NeurIPS_1

The expected annual base salary for this position is USD 250,000 – USD 600,000. Our compensation package also includes variable compensation in the form of sign-on and year-end bonuses, and generous benefits, including relocation and immigration assistance. The applicable annual base salary paid to a successful applicant will be determined based on multiple factors including the nature and extent of prior experience and educational background. We follow a hybrid work schedule, in which employees work from the office on Tuesday through Thursday, and have the option of working from home on Monday and Friday.

D. E. Shaw Research, LLC is an equal opportunity employer.

Join Shopify's Machine Learning Post-Grad Internship: Lead the Next Wave of AI Innovation in E-commerce

At Shopify, we're not just building models; we're redefining the e-commerce landscape with AI. As a Masters/PhD Research Intern, you'll engage with petabyte-scale data, leveraging cutting-edge ML/AI methods to develop and deploy models that impact millions. You'll push boundaries using technologies like LLM post-training, reinforcement learning, and model quantization.

Pair your research with real-world problems and data:

Engage in research that ties to real-world problems today that impact our merchants and customers worldwide.

Collaborate and Deliver:

Work side by side with engineers, applied scientists, and other teams to work with you on your research experiments or prototypes with the idea to get your work into production in the longer term.

Create and Learn:

Solve tangible problems that require longer-term research that require you to design, build, and deploy models. Do this in production or as a proof of concept.

Share and Grow:

Stay up to date with the latest techniques, learn trade-offs between models and techniques IRL and share with others at Shopify to make everyone better.

About You:

• You're pursuing or have completed a Master’s or Doctorate in Computer Science, Computer Engineering, or a relevant technical field.
• Your research experience spans areas like Machine Learning, Search, NLP, Recommendation Systems, Pattern Recognition, Agents, LLM or Gen AI.
• You have hands-on experience with ML frameworks such as PyTorch, TensorFlow, or equivalent.
• You're adept at translating insights into business recommendations and have experience with systems software or algorithms.
• You have a proven track record of building and shipping high-quality, reliable work.
• You excel in programming languages like Python, R, or MATLAB and can independently identify, design, and complete medium to large features.
• You have demonstrated experience through internships, work, conferences, papers, coding competitions, or open-source contributions.
• You enjoy solving complex problems and comparing alternative solutions to determine the best path forward.

Our Internship Experience:

• Unique Matching Process: We pair you with teams where you'll thrive, aligned with both your skills and Shopify's needs.
• Flexible Work Environment: Post-onboarding, work in-office three days a week at your choice, coordinating with your Manager and Mentor for optimal team synergy.
• Legally Eligible: You must be authorized to work in Canada or the US for the internship duration. We don't offer immigration support for interns.
• Locations: Interns work from our offices in Bellevue, NYC, or Toronto. Relocation to the closest office is necessary if not already based there.

Application Essentials:

• Prepare Your Resume: Include it in your application.
• Complete All Application Questions: Ensure nothing is left unanswered.
• Engage with Assessments: If you advance, complete mandatory assessments to showcase your technical prowess.

Why Apply?

• Shape the future of e-commerce with cutting-edge AI solutions.
• Work in a dynamic, innovative environment that values creativity and experimentation.
• Enhance your skills with hands-on experience and professional growth opportunities.

Application timeline: Applications are open from Tuesday, December 2, 2025 - December 5, 2025.

At Shopify, we're not just offering internships; we're crafting the future. Join us, and let's build what's next.