About AIMATX

AIMATX is a Berkeley-based startup revolutionizing materials science by creating next-generation materials and molecules that power the future economy. Our AI-driven platform explores vast chemical spaces, predicts new materials and their properties, and accelerates discovery through intelligent, targeted experimentation. By reducing years of R&D to weeks, we are shaping the future of materials innovation; come join us!

AIMATX is built and guided by a world-class team at the intersection of science, AI and engineering. Our leadership includes Omar Yaghi (2025 Nobel Prize), Fernando Perez, inventor of Jupyter/IPython, alongside former CEOs of public companies and leading researchers in generative AI and autonomous experimentation. This ecosystem brings unmatched scientific depth, computational expertise, and entrepreneurial excellence to accelerate the future of discovery.

Role Overview

We are seeking a Machine Learning Engineer with deep expertise in large-scale generative models (e.g., LLMs, diffusion models) to join our innovative team. You will design, build, and scale the core AI systems that power our materials discovery engine, enabling rapid experimentation, robust deployment, and continuous improvement. As part of our technical team, you will:

• Design and implement training pipelines for LLMs, diffusion models and related architectures for molecular, materials and experimental design.
• Build robust data pipelines and preprocessing workflows for multimodal scientific data.
• Optimize model training and inference at scale, including distributed training and mixed-precision acceleration.
• Develop evaluation, benchmarking and monitoring frameworks to assess reliability, calibration and performance of generative models.
• Collaborate with scientists and engineers to integrate models into self-driving lab workflows and closed-loop experimentation.
• Work closely with MLOps and platform teams to ensure reproducibility, experiment tracking and scalable deployment.
• Stay current with advances in LLMs, diffusion models, reinforcement learning and agentic AI, and translate promising ideas into production systems.
• Maintain high engineering standards, including testing, documentation and code review.

Required Qualifications

• Degree in Computer Science, Machine Learning, Applied Mathematics, Engineering or a related technical field (or equivalent practical experience).
• Strong software engineering experience building and maintaining ML systems in production.
• Expertise with deep learning frameworks such as PyTorch or JAX.
• Proficiency with Python and experience working in collaborative, large-scale codebases.
• Demonstrated track record of owning and delivering end-to-end ML projects from prototype to production.

Preferred Qualifications

• Experience working with generative models in chemistry or materials science.
• Background or strong interest in scientific domains (chemistry, materials science, physics, biology) or scientific ML.
• Contributions to open-source ML or infrastructure projects, or publications in ML/AI conferences or journals.
• Expertise in training large-scale generative models (e.g., LLMs, diffusion models).

Soft Skills & Cultural Fit

• Excellent written and verbal communication skills.
• Collaborative mindset and ability to work effectively in a multidisciplinary team.
• Proactive and self-motivated, with the ability to take initiative.
• Commitment to scientific rigor, innovation and continuous learning.

Benefits & Perks

We offer a competitive salary with bonus potential and meaningful early equity. Compensation reflects experience, expertise and expected impact.

Additional benefits may include: - Flexible work arrangements and remote options. - Medical, dental, and vision coverage. - 401(k) with company matching. - Generous PTO and parental leave.

How to Apply

Send your CV to theo.jaf@aimatx.ai

Waddle Labs: - we are an early-stage startup - we build robotics models to solve physical bottlenecks in science (eg. wet lab experiments) - YC W26

The other companies on this career site know what they're doing. We don't. Do you want to help us figure it out?

If you want to find out more, reach out to wave@waddlelabs.ai with 1 sentence about what you’re interested in.

Stellenbosch University, South Africa

The Department of Mathematical Sciences at Stellenbosch University (South Africa) has a 2-year postdoctoral position available in the area of machine learning for wildlife monitoring and conservation. The project will look at:

zero-shot capabilities of foundation models on challenging real-world datasets typical in African wildlife and environment monitoring (e.g., camera trap imagery);

few-shot learning and generative modelling to deal with these large, unlabelled, long-tailed, noisy image sets.

Applicants must have obtained a PhD degree within the last 4 years, in a field related to the project's themes. The fellowship must commence by 1 March 2026 (preferably sooner).

Applications and supporting documents can be submitted through this online form.

Applications close 15 December 2025.

Enquiries: Prof. Willie Brink (wbrink@sun.ac.za).

NVIDIA is searching for an outstanding researcher working on efficient deep learning to join the deep learning efficiency research team. We are passionate about research that pushes boundaries but also has impact in the real world. We are particularly excited about methods for post-training model optimization (pruning, quantization, NAS), efficient architecture design, adaptive/dynamic inference, resource-efficient training and finetuning, and so forth. You will work within an amazing and collaborative research team that consistently publishes at the top venues in computer vision and machine learning. Our existing expertise includes computer vision, deep learning, generative models, and so forth. Your contributions have the chance to create real impact on our products.

What you'll be doing: Research, design and implement novel methods for efficient deep learning.

Publish original research.

Collaborate with other team members and teams.

Mentor interns.

Speak at conferences and events.

Work with product groups to transfer technology.

Collaborate with external researchers.

What we need to see: Completing or recently completed a Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or have equivalent research experience.

Excellent knowledge of theory and practice of computer vision methods, as well as deep learning.

Background in pruning, quantization, NAS, efficient backbones, and so on, is a plus.

Experience with large language models and large vision-language models is required.

Excellent programming skills in Python and PyTorch; C++ and parallel programming (e.g., CUDA) is a plus.

Hands-on experience with large-scale model training including data preparation and model parallelization (tensor and pipeline) is required.

Outstanding research track record.

Excellent communications skills.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world working for us. If you're creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

The base salary range is 160,000 USD - 258,750 USD.

You will also be eligible for equity and benefits.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Palo Alto

Our formula for success is to hire exceptional people, encourage their ideas and reward their results.

As an AI Research Intern, you will be an integral member of a team of experienced technologists, quantitative researchers, and traders. You will collaborate closely with other researchers to solve challenging AI and machine learning problems. Your projects will vary depending on priorities at the start of your employment and could include solving forecasting problems or developing large language models (LLMs). We are looking for individuals eager to learn new AI technologies, create innovative solutions, and choose the right tools to directly impact our business. You will be surrounded by cutting-edge technology, given immediate responsibility, mentored by industry-leading experts, and attend a robust training program to ensure your success at DRW.

How you will make an impact… Algorithm Development: Creating and testing new AI models and algorithms to solve specific problems or improve existing methods. Data Engineering: Building data pipelines for model training and evaluation, including data collection, cleaning, preprocessing, and labeling, while contributing to better data management practices. Model Testing & Evaluation: Designing and implementing rigorous testing frameworks to assess model performance and identify areas for improvement. Collaboration: Working closely with team members to establish and refine research methodologies, promoting peer reviews, testing, and thorough documentation. Research & Learning: Staying updated on the latest AI techniques and advancements, sharing insights, and actively bringing improvements to research processes.

What you bring to the team… Are pursuing a PhD in artificial intelligence, machine learning, computer science, or a related field graduating between December 2026 and June 2027. Strong foundation in AI concepts. Strong knowledge of machine learning. Solid technical and programming skills (Python, Java, GitHub). Familiarity with machine learning framework (Spark, PyTorch, etc.). Excellent analytical, problem-solving, and communication skills. Deep interest in financial markets.

Preferred Skills: Experience with NLP tasks Knowledge of TensorFlow or PyTorch. Basic understanding of MLOps principles (monitoring, versioning, model serving).

Learning Opportunities: Gain in-depth experience with cutting-edge ML/AI techniques and model deployment. Develop robust machine learning research skills, from data engineering to model evaluation, while contributing to advancements in AI methodologies and practices. Contribute to research projects with potential impact on financial decision-making and other applied domains. Engage in fostering a collaborative research culture, driving improvements in research quality, and interdisciplinary collaboration.

What to expect during the internship Meaningful projects: Each project, advised by a trader, promotes a comprehensive learning experience and provides you with real-world work experience. Community: Throughout the summer, we host a variety of educational, social and team-building activities to explore the city, foster friendships and camaraderie. Housing: DRW provides fully furnished apartments located close to the office – making your morning commute as easy as possible. Mentorship: You’ll build a professional relationship with an experienced mentor in your field. Mentors and mentees meet to discuss goals, challenges and professional development and explore the city together at our mentor outings. Education: As the trading industry continually evolves, both in terms of new products and transaction methods, the future will present us with unique opportunities and challenges. You’ll complete an options course taught by an experienced trader and participate in a technology immersion course to better understand how technology and trading intersect.

Pittsburgh, PA

US Citizenship required (green card or visa does not suffice)

Work with the world leaders in computational game theory on software products for real problems of importance! Positions are available for working on the nation's best fighter pilot AI, on wargaming, on command and control, on missile defense, and on optimizing the world's nuclear stability. Work on the most important problems in the world! The work leverages the leading course-of-action generation and execution AI system, which we have developed.

Required qualifications:

• Degree as indicated in the position announcement roles

• Strong software development skills

• Excitement to change the world with AI products

• Desire to work with the world's leading experts in a fast-moving environment

• US citizenship (green card or visa does not suffice), and eligibility to obtain Top Secret clearance

Why apply?

• The company is the world leader in computational game theory AI

• Unique opportunity to apply game theory-based software products to the real world

• Ability to work directly with world-leading AI experts

• The company is already profitable

• CMU startup in close proximity to CMU

• Competitive compensation, including equity in a fast-moving, profitable startup

• The company has a no-jerks policy

** Our Founder, President, and CEO, Dr. Tuomas Sandholm, will be available to conduct interviews personally at NeurIPS between December 4th and 7th, 2025, and additional positions will be available thereafter as well. **

San Jose, CA, USA

Adobe is looking for a Senior Machine Learning Engineer to help shape the future of agentic AI in the enterprise. In this role, you will design, build, and scale cutting-edge platforms and products that redefine how enterprises create and optimize customer experiences and marketing campaigns. You will play a key role in advancing AEP Agent Orchestrator—a foundational platform layer that manages and connects Adobe and third-party agents. You will work in a fast-moving, high-impact environment with a team of talent engineers and applied scientists where creativity, collaboration, and data-driven innovation come together to make a real difference.

What you'll do

• Design and development of state-of-the-art agentic AI system and platform powered by generative AI, including working on engineering problems such as defining APIs, integrating with UIs, deploying Cloud services, CICD, etc., as well as implementing ML- and LLM-Ops best practices, delivering high quality, production ready code.

• Design and build ML workflows for enterprise-scale model customization, serving, and ecosystem integration.

• Partner with researchers and applied scientists on productization of innovations

• Engage in the product lifecycle, design, deployment, and production operations.

What you need to succeed

• The ideal candidate will have the following background:

• PhD or MS degree in Computer Science or related field required.

• 5+ years of experience in machine learning, including production-scale deployments

• Experience with agile development, and short release cycles

• Good understanding of statistical modeling, machine learning, or analytics concepts; ability to quickly learn new skills and work in a fast-paced team.

• Proficient in one or more programming languages such as Python and Java. Familiarity with cloud development on Azure/AWS.

• Experience using Relational (MySQL, Postgres) and NoSQL datastores (Redis, ElasticSearch, Snowflake) along with data access patterns and strategies

• Experience working with at least one deep learning framework such as TensorFlow or PyTorch.

• Experience with LLMs including prompt/context-engineering, modern LLM APIs, fine-tuning models etc.

• Experience working with both research and product teams.

• Excellent problem-solving and analytic skills

• Excellent communication and relationship building skills.

Location USA, WA, Seattle

Description The Amazon Connect Interactive AI and Engagement organization was formed in April 2025 to bring together Contact Lens, Q in Connect, and Flows/Lex into one organization, responsible for weaving native-AI across the Connect application experiences delivered to end-customers, agents, and managers/supervisors. We are reimagining customer engagement to enable companies to deliver proactive and personalized experiences (in websites, mobile apps, and traditional contact center channels including voice, messaging, and email) that discern and resolve end-customers' intent before problems ever arise. To succeed, we need a unified science strategy and approach to power 'AI-throughout' customer experiences that leverage humans in the loop when required to meet business goals. We seek to hire a Director of Applied Science who will define and execute that strategy, and organization required. This leader will push the technical boundaries in generative AI science, shaping the industry, while influencing and leading key product investments across Connect service teams and leadership.

The business opportunity is substantial. We are executing to be the leader irrespective of the ultimate balance between proactive end-customer self-service and agent-assisted workloads. To do so, science innovation will be pivotal to help achieve our ambitious goals, differentiating Amazon Connect from our competitors.

Introduction of School (located in Shenzhen, China)

The School of Artificial Intelligence (SAI) of The Chinese University of Hong Kong, Shenzhen was founded on February 13, 2025. (https://sai.cuhk.edu.cn/)

The School is committed to addressing the critical national strategic needs and advancing the international frontiers in artificial intelligence. Rooted in the strategic development plan of the Guangdong-Hong Kong-Macao Greater Bay Area and leveraging the industrial strengths of the vibrant Shenzhen Special Economic Zone, the School builds on the solid academic foundation of The Chinese University of Hong Kong, Shenzhen to advance AI foundations and technologies. With a strong emphasis on internationalization, the School aims to create an interdisciplinary and innovative learning environment that equips students with a solid foundation in computer science, mathematics, statistics, and cognitive science, enabling them to fully grasp the principles and applications of AI.

The School strives to elevate China’s teaching and research capabilities in AI through a series of systematic, original breakthroughs with significant international impact. It aims to nurture top-tier professionals and interdisciplinary talents for the nation, the Greater Bay Area, and Shenzhen, providing a continuous supply of talent and research support for the sustainable development of the AI industry.

Post Specification (Application link: https://jobs.cuhk.edu.cn/jobDetails?id=285, contact us: talent4sai@cuhk.edu.cn)

Newly established, The School of Artificial Intelligence (SAI) at The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen) is pleased to invite applications for full-time faculty positions at all academic ranks with multiple positions. We welcome candidates with expertise in, but not limited to, the following areas:

l Natural Language Processing (NLP): Large language models (LLMs), sentiment analysis, multilingual AI, and generative AI.

l Machine Learning and AI Foundations: Reinforcement learning, transfer learning, representation learning, trustworthy/explainable AI, and computational cognitive science.

l Embodied AI: Human-robot interaction, multi-modal perception, and AI for autonomous decision-making systems.

l Large-scale AI and Distributed Machine Learning: Scalable AI systems, distributed computing architectures, and multi-agent learning frameworks.

l Robotics and Autonomous Systems: Motion planning, intelligent navigation, embodied intelligence, robot design, nano-robots, swarm robotics, medical robotics, and AI for dynamic environments.

l AI Ethics and Society: Fairness, accountability, transparency, and the social implications of AI technologies.

l Emerging AI Paradigms: Neuro-symbolic AI, lifelong learning, quantum AI, and cognitive-inspired computing models.

l AI and Applications: AI for Science, AI for Business and Economics, AI for Medicine, AI for Society, etc.

l Signal Processing: AI-driven statistical signal processing, graph signal processing, and data-driven signal analysis for complex systems.

l Mathematical Sciences: Statistics, advanced computational mathematics, numerical optimization techniques, and mathematical foundations for AI and machine learning.

Qualified candidates have a doctoral degree in Computer Science, Electrical Engineering, Mathematical Science, and other related fields, complemented by postdoctoral training and relevant work experience in related research areas. Applicants for professorships at the rank of Professor or Associate Professor are expected to have an established research program with a funding history, independent research and teaching experiences, and an excellent publication record. We also welcome candidates with teaching experience in related fields for Lecturer and Assistant Professor (Teaching) positions.

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