Bala Cynwyd (Philadelphia Area), Pennsylvania United States

Overview

Susquehanna is expanding the Machine Learning group and seeking exceptional researchers to join our dynamic team. As a Machine Learning Researcher, you will apply advanced ML techniques to a wide range of forecasting challenges, including time series analysis, natural language understanding, and more. Your work will directly influence our trading strategies and decision-making processes.

This is a unique opportunity to work at the intersection of cutting-edge research and real-world impact, leveraging one of the highest-quality financial datasets in the industry.

What You’ll Do

Conduct research and develop ML models to enhance trading strategies, with a focus on deep learning and scalable deployment 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 Develop automation tools to streamline research and system development Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior Partner with engineering teams to implement and test models in production environments

What we're looking for We’re looking for research scientists with a proven track record of applying deep learning to solve complex, high-impact problems. The ideal candidate will have a strong grasp of diverse machine learning techniques and a passion for experimenting with model architectures, feature engineering, and hyperparameter tuning to produce resilient and high-performing models.

PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry settings, with 5+ years of experience building impactful deep learning systems A strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR Strong programming skills in Python and/or C++ Practical knowledge of ML libraries and frameworks, such as PyTorch or TensorFlow, especially in production environments Hands-on experience applying deep learning on time series data Strong foundation in mathematics, statistics, and algorithm design Excellent problem-solving skills with a creative, research-driven mindset Demonstrated ability to work collaboratively in team-oriented environments A passion for solving complex problems and a drive to innovate in a fast-paced, competitive environment

Postdoctoral Scholar: Computational Medicine Research Group, University of California, Irvine (NIH Funded)

The Computational Medicine Research Group directed by Prof. Pratik Shah at the University of California, Irvine, invites applications for an NIH-funded Postdoctoral Scholar position. We seek outstanding Ph.D. candidates in computer science, biomedical informatics, statistics, or related fields to develop novel deep learning and AI technologies for digital biopsies from medical images and clinical decision-making from non-imaging datasets. Research areas include:

• Generative AI for Medical Imaging & Digital Biopsies: Developing and interpreting DNNs for automated tissue analyses using high-parameter images (pathology, MRI, CT, RGB) and validating these models in collaboration with hospitals nationwide.

• Generative & Predictive AI for Clinical Decision Support: Developing biologically informed statistical methods and uncertainty estimation generative models for explainable clinical decision-making from EMRs and genetic data.

Responsibilities include data preprocessing, training and real-world validation of generative deep learning models (GANs, Diffusion models, Transformers), developing novel statistical models, and publishing research in leading journals and conferences. Comprehensive training in publication, fellowship and grant writing, and career development for roles in academia, industry, or government will be provided.More information about the lab can be found at https://faculty.sites.uci.edu/pratikshahlab/

The role We seek an experienced AI/ML Specialist Solutions Architect to support AI-focused customers leveraging Nebius services. In this role, you will be a trusted advisor, collaborating with clients to design scalable AI solutions, resolve technical challenges and manage large-scale AI deployments involving hundreds to thousands of GPUs.

You’re welcome to work remotely from the United States or Canada.

Your responsibilities will include: - Designing customer-centric solutions that maximize business value and align with strategic goals. - Building and maintaining long-term relationships to foster trust and ensure customer satisfaction. - Delivering technical presentations, producing whitepapers, creating manuals and hosting webinars for audiences with varying technical expertise. - Collaborating with engineering and product teams to effectively prioritize and relay customer feedback.

We expect you to have: - 7-10 + years of experience with cloud technologies in MLOps engineering, Machine Learning engineering or similar roles. - Strong understanding of ML ecosystems, including models, use cases and tooling. - Proven experience in setting up and optimizing distributed training pipelines across multi-node and multi-GPU environments. - Hands-on knowledge of frameworks like PyTorch or JAX. - Excellent verbal and written communication skills.

It will be an added bonus if you have: - Expertise in deploying inference infrastructure for production workloads. - Ability to transition ML pipelines from POC to scalable production systems.

Preferred tooling: - Programming Languages – Python, Go, Java, C++ - Orchestration – Kubernetes (K8s), Slurm - DevOps Tools – Git, Docker, Helm - Infrastructure as Code (IaC) – Terraform - ML Frameworks and Libraries – PyTorch, TensorFlow, JAX, HuggingFace, Scikit-learn

Bala Cynwyd (Philadelphia Area), Pennsylvania United States

Overview

We’re looking for a Machine Learning Systems Engineer to strengthen the performance and scalability of our distributed training infrastructure. In this role, you'll work closely with researchers to streamline the development and execution of large-scale training runs, helping them make the most of our compute resources. You’ll contribute to building tools that make distributed training more efficient and accessible, while continuously refining system performance through careful analysis and optimization. This position is a great fit for someone who enjoys working at the intersection of distributed systems and machine learning, values high-performance code, and has an interest in supporting innovative machine learning efforts.

What You’ll Do

Collaborate with researchers to enable them to develop systems-efficient models and architectures Apply the latest techniques to our internal training runs to achieve impressive hardware efficiency for our training runs Create tooling to help researchers distribute their training jobs more effectively Profile and optimize our training runs

What we're looking for Experience with large-scale ML training pipelines and distributed training frameworks Strong software engineering skills in python Passion for diving deep into systems implementations and understanding fundamentals to improve their performance and maintainability Experience improving resource efficiency across distributed computing environments by leveraging profiling, benchmarking, and implementing system-level optimizations

Why Join Us?

Susquehanna is a global quantitative trading firm that combines deep research, cutting-edge technology, and a collaborative culture. We build most of our systems from the ground up, and innovation is at the core of everything we do. As a Machine Learning Systems Engineer, you’ll play a critical role in shaping the future of AI at Susquehanna — enabling research at scale, accelerating experimentation, and helping unlock new opportunities across the firm.

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.

Postdoctoral Research Fellow

Icahn School of Medicine at Mount Sinai — Department of Artificial Intelligence and Human Health
Location: New York, NY

The Liu Lab in the Department of Artificial Intelligence and Human Health at the Icahn School of Medicine at Mount Sinai is recruiting a Postdoctoral Research Fellow. Our lab develops interpretable artificial intelligence frameworks that integrate digital health data (e.g., wearable sensor time-series), genomics, and electronic health records to advance discovery in complex neurological and psychiatric disorders, including depression, ADHD, Parkinson’s disease, and Alzheimer’s disease.

The postdoc will contribute to projects involving large-scale digital phenotyping, multimodal data integration, advanced time-series modeling, and AI-driven identification of biological and clinical markers of disease risk, progression, and treatment response.

Interested applicants may email their CV to contact@liujlab.org.

Responsibilities

• Develop and implement AI/ML models for high-dimensional time-series, genomic, and clinical data
• Perform data preprocessing, analysis, and multimodal integration
• Develop interpretable and explainable ML methods for biomedical applications
• Build computational pipelines, reproducible workflows, and internal tools
• Prepare manuscripts, figures, and visualizations for publications and presentations
• Collaborate with faculty, clinicians, and researchers across Mount Sinai
• Participate in lab meetings, seminars, workshops, and collaborative projects

Required Qualifications

• PhD in Computer Science, Computational Biology, Bioinformatics, Statistics, Biomedical Data Science, Neuroscience, or a related quantitative field
• Strong programming skills (e.g., Python, R)
• Background in machine learning, deep learning, statistical modeling, or related areas
• Experience working with large datasets and computational tools
• Strong written and oral communication skills

Preferred Experience

• Demonstrated experience in AI/ML, data science, or computational biology
• Experience with time-series modeling, genomics, digital health, or multimodal data (preferred but not required)

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. Please visit the Qualcomm NeurIPS home page by clicking the URL to apply.

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

3. Apply to any of the linked positions on our Qualcomm NeurIPS home page. Make sure you REGISTER first before applying. Your resume will stand out.

The role We are seeking a highly skilled and customer-focused professional to join our team as a Cloud Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.

You’re welcome to work remotely from the US or Canada.

Your responsibilities will include: - Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices. - Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers. - Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI. - Act as a single point of expertise of customer scenarios for product, technical support, marketing teams. - Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)

We expect you to have: - 5 - 10 + years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing - Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python - Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL) - Excellent communication skills - Customer-centric mindset

It will be an added bonus if you have: - Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow) - Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch) - Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google)

London

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.

Location Bay area or remote

Description

Goaly AI is hiring multiple AI research & AI infra positions, full-time and intern!

=== About Goaly === We are an early-stage stealth mode AI startup located in Silicon Valley, founded by ex-FAANG AI engineers & researchers who have led multiple GenAI products from research to production, powering billion-user products. We are backed by accredited investors and AI leadership from top tech firms, primarily serving rising AI labs and enterprise clients. We are on a mission to make frontier AI accessible and affordable to every business.

=== Why This Matters for Your Research === You will own end-to-end LLM/SLM development, working on cutting-edge model architectures and novel optimization techniques. Your research is backed by abundant GPU clusters, and we offer full support to publish breakthrough results at top conferences, including NeurIPS, ICML, and CVPR.

We are a super fun team that work and play hard together. We are actively hiring AI researchers and AI infra engineers (intern and full-time). Our job postings: https://goaly.ai/jobs?job_function=research
Send your cool projects / resume to recruiting@goaly.ai and lets YOLO together!