Various locations available

Adobe Researchers are developing the next generation of advanced technologies and user experiences, inventing a future where Adobe enables new forms of creativity, frees people from routine tasks, and allows enterprises to understand and act quickly on customer and business insights. Our research labs are actively published in leading journals and conferences, work with product teams on high profile features, and explore new product opportunities across various domains. We are especially interested in fostering ongoing collaborations that last beyond the internship and become part of your PhD thesis.

Adobe Research focuses on the following research areas: - Content Intelligence - AI & Machine Learning - Computer Graphics (2D&3D) - Data Intelligence - Computer Vision, Imaging & Video - Audio - Systems and Languages - Natural Language Processing - Human Computer Interaction - AR, VR & 360 Photography - Document Intelligence - Intelligent Agents & Assistants

What you will do

Under the direction of an Adobe Research mentor, you will: - Pursue a research problem to apply to Adobe’s products and with the possibility of academic publication - Develop new algorithms, run experiments, and produce demonstration prototypes - Document and present your work, both verbally and in writing

What you will need - Current PhD or master's student in computer science, or related field (exceptional undergraduates will also be considered) - Sufficient research skills and background in your chosen subject area - Strong communication skills and teamwork experience - Passion for solving real-world problems with web-scale data using and inventing innovative Machine Learning algorithms.

Palo Alto, CA

Position Description: Tesla is looking for strong Machine Learning Engineers to help build foundation models for robotics to drive the future of autonomy across all current and future generations of vehicles. You will work on a lean team without boundaries and have access to one of the world’s largest training clusters. Most importantly, you will see your work repeatedly shipped to and utilized by millions of Tesla’s customers.

Responsibilities: Leverage millions of miles of driving data and interventions to build a robust and scalable end-to-end learning based self-driving system Use cutting-edge techniques from generative modeling, imitation learning, and reinforcement learning to improve the planning and reasoning capabilities of our driving models Experiment with data generation and fleet data collection approaches to enhance the diversity and quality of training data Integrate directly with vehicle firmware and ship production quality, safety-critical software to the entirety of Tesla's vehicle fleet

Requirements: Strong experience with Python, any major deep learning framework, and software engineering best practices An "under the hood" knowledge of deep learning modern architectures, optimization, model alignment, etc. Proven expertise in deploying production ML models for self-driving, robotics, or natural language processing at scale Comfort with C++ to help integrate with vehicle firmware and take projects from ideas to shipped products

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

New York

The D. E. Shaw group seeks exceptional software engineers with expertise in applied AI, AI agents, and agentic systems to join the firm. This role offers the chance to work directly with a variety of groups at the firm on innovative, greenfield projects that transform how teams operate—leveraging quantitative and programming skills to design, build, and deploy AI solutions that drive efficiency, enhance analytical capabilities, and accelerate decision-making across the firm.

What you’ll do day-to-day

You’ll join a dynamic team, with the potential to:

• Collaborate directly with internal groups and end users across various functions to build bespoke AI agents and applications tailored to nuanced, real-world business needs.
• Lead and contribute to greenfield AI projects, taking ownership from concept through production and helping shape internal AI strategy and adoption.
• Experiment with emerging AI tools and model capabilities, rapidly prototyping and integrating them across platforms to enhance usability, scalability, and effectiveness.
• Scale the adoption of AI tools firmwide by developing best practices, frameworks, and reusable components that drive innovation and productivity.
• Build foundational AI components, such as agent frameworks, reusable “skills,” and large-scale retrieval systems, to support AI tools and applications.
• Design, develop, and maintain shared AI infrastructure and agentic applications, ensuring firmwide data integration and enhancing software development efficiency.

Who we’re looking for

• A bachelor’s degree in any field is required, along with an extensive background in software development, and hands-on experience building and scaling AI solutions at the product, system, or company level.
• Solid understanding of AI technologies and an interest in developing advanced AI applications and frameworks.
• Demonstrated ability to thrive in technical or entrepreneurial environments, along with the capability to solve complex challenges and lead projects from inception to deployment.
• A record of strong academic or professional achievement, with analytical depth and creativity in AI-related projects.
• We welcome outstanding candidates at all experience levels who are excited to work in a collegial, collaborative, and fast-paced environment.
• The expected annual base salary for this position is USD 200,000 to USD 250,000. Our compensation and benefits package includes variable compensation in the form of a year-end bonus, guaranteed in the first year of hire, and benefits including medical and prescription drug coverage, 401(k) contribution matching, wellness reimbursement, family building benefits, and a charitable gift match program.

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.

Location Beijing CHINA

Description

1. Mission and Positioning： The Beijing Academy of Artificial Intelligence (BAAI) invites strategic scientists from the global AI community to join us as a Chief Scientist. In this role, you will chart the future course for the Academy's and the discipline's development, guiding our exploration of the AI frontier and establishing yourself as an academic leader shaping the global AI landscape.

2. Qualifications：

3. A distinguished research background at world-leading universities, national-level research institutions, or corporate R&D labs of global renown.
4. A proven record of publishing a series of highly influential research findings in top-tier AI journals and conferences, with the ability to define the frontiers of the discipline.

5. Visionary strategic insight and exceptional academic leadership, with a demonstrated capacity to identify and tackle the field's most fundamental challenges.

6. We Offer：

7. A globally competitive compensation package and comprehensive benefits (customized arrangements are available).
8. Full academic autonomy supported by substantial, long-term research funding and access to world-class computing infrastructure.
9. Full support to assemble and lead an elite research team from around the world.
10. Expedited Beijing residency registration for eligible candidates and access to a premium medical "Green Channel" for senior talent.

11. Customized supplementary health insurance plans for experts and their immediate family members.

12. How to Apply： Please send your detailed CV, representative publications, and a brief research vision statement to: [recruiting@baai.ac.cn] Use the email subject line: "Chief Scientist Application - [Name] - [Primary Research Field]"

Research Fellow

Job Reference: 521360
Employment Type: Full Time (Fixed Term, 2 Years)
Location: Perth, Western Australia

Remuneration

Base salary: Level B, $118,150–$139,812 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 research and development of advanced computer vision models, multi-object tracking, and post-processing methods to improve traffic video analytics in complex environments. You will drive benchmarking, evaluation, and deployment optimisation of AI models, ensuring scalability and real-world performance. You will publish research, mentor junior staff, and collaborate with engineers and partners to translate innovations into production-ready solutions.

Selection Criteria

Essential:

• Tertiary degree in Computer Science, Applied Mathematics/Statistics, Robotics, Physics, or related discipline, with excellent academic record
• Demonstrated expertise in computer vision and machine learning, including object detection, segmentation, and multi-object tracking in challenging conditions such as occlusions, crowded scenes, and object re-identification
• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow) and Python ML libraries (e.g., NumPy, OpenCV, scikit-learn)
• Experience implementing and evaluating state-of-the-art tracking algorithms such as DeepSORT, ByteTrack, and Transformer-based approaches
• Proven ability to design and run rigorous experimental frameworks, including benchmarking, ablation studies, and field validation

Further Information

Position Description: PD [Research Fellow] [521360].pdf

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

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.

New York

Quantitative Researchers (QRs) specialize in a variety of areas, including but not limited to: using sophisticated data analysis skills to build predictive models, driving construction of a complex multi asset portfolio by utilizing large scale portfolio optimization techniques, and developing sophisticated optimization algorithms. Researchers with an exceptional record of achievement in their respective fields and a drive to apply quantitative techniques to investing are encouraged to apply to GQS.

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