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.

Location Seattle, WA, United States San Francisco, CA, United States

Description We are seeking a visionary leader to spearhead post training model research and development efforts. As the post training science lead, you will be responsible for driving the development and implementation of cutting-edge methodologies around improving model performance based on human feedback. You will lead a team of world-class scientists in exploring new frontiers of code generation for the most popular languages simplifying documentation, unit testing, optimizing existing code, explaining code and simplifying way users interact with the database systems enabling natural language interface. Responsibilities

Responsibilities

Research and Development: Conduct in-depth research on code generation techniques, including code to code (Java, SQL, Python, etc.), doc to code/code to doc, and other emerging approaches. Model Development: Design, develop, and train state-of-the-art code generation models that meet the highest quality standards. Team Leadership: Build and mentor a high-performing team of scientists and engineers. Collaboration: Work closely with cross-functional teams to integrate code generation capabilities into various applications and products. Innovation: Identify new opportunities for image generation and explore emerging technologies. Stay Updated: Maintain a deep understanding of industry trends and advancements in code generation.

Qualifications and Experience:

PhD Computer Science, Mathematics, Statistics, Physics, Linguistics or a related field with a dissertation, thesis or final project centered in Machine Learning and Deep Learning) with 5+ years relevant experience is preferred but not a must; OR Masters or Bachelor’s in related field with 8+ years relevant experience Strong publication record, including as a lead author or reviewer, in top-tier journals or conferences. Extensive experience in image generation, computer vision, and deep learning Proven track record of leading research and development projects Strong understanding of machine learning algorithms and architectures Excellent problem-solving and analytical skills Strong leadership and communication abilities

If you are passionate about pushing the boundaries of image generation and have a proven track record of success, we encourage you to apply. Qualifications Disclaimer:

Certain US customer or client-facing roles may be required to comply with applicable requirements, such as immunization and occupational health mandates.

Range and benefit information provided in this posting are specific to the stated locations only

US: Hiring Range in USD from: $120,100 to $251,600 per annum. May be eligible for bonus, equity, and compensation deferral.

Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle’s differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity.

Oracle US offers a comprehensive benefits package which includes the following: 1. Medical, dental, and vision insurance, including expert medical opinion 2. Short term disability and long term disability 3. Life insurance and AD&D 4. Supplemental life insurance (Employee/Spouse/Child) 5. Health care and dependent care Flexible Spending Accounts 6. Pre-tax commuter and parking benefits 7. 401(k) Savings and Investment Plan with company match 8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for sub

You’re welcome to work remotely from Amsterdam, Netherlands - Europe; United Kingdom

The role

This role is for Nebius AI R&D, a team focused on applied research in AI. Examples of applied research that we have recently published include: - applying reinforcement learning for agent training in long-context multi-turn scenarios - dramatically scaling task data collection to power reinforcement learning for SWE agents - building a decontaminated evaluation for SWE agents that is regularly updated - investigating how test-time guided search can be used to build more powerful agents The results often lead to collaboration with adjacent teams where our research findings are applied in practice.

We are currently looking for senior- and staff-level ML engineers to work on research in areas such as: - Guided search and reinforcement learning for agentic systems - Reinforcement learning for reasoning models - Web-scale problem collection for training agents - Efficient model distillation

Some examples of what your responsibilities might include are: - Conducting experiments to figure out efficient ways to train a large language model on traces of interactions with various environments - Exploring methods of guided generation and search in the trajectory space - Coming up with ways to mine relevant data at web scale and figuring out efficient ways to use this data in model post-training - Conducting experiments with different reinforcement learning configurations in verifiable domains - Exploring methods to train AI agents on tasks with non-verifiable reward signals

We expect you to have: - A profound understanding of theoretical foundations of machine learning and reinforcement learning - Deep expertise in modern deep learning for language processing and generation - Substantial experience with training large models on multiple computational nodes - Strong software engineering skills (we mostly use python) - Deep experience with modern deep learning frameworks (we use jax) - Strong communication and leadership abilities - Experience designing, executing, and analyzing machine learning experiments with proper statistical rigor - Ability to formulate research questions, design experiments to test hypotheses, and draw meaningful conclusions from results - Ability to document research findings clearly and contribute to technical publications or report

Nice to have: - Experience with deep reinforcement learning for LLMs, including techniques such as reward modeling, DPO, PPO etc - Familiarity with important ideas in LLM space, such as RoPE, ZeRO/FSDP, Flash Attention, quantization - Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field Master’s or PhD preferred - Track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment - Experience in engineering complex systems, such as large distributed data processing systems or high-load web services - Open-source projects that showcase your engineering prowess - Excellent command of the English language, alongside superior writing, articulation, and communication skills - Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing

The College of Information Science at the University of Arizona invites applications for multiple tenure track Assistant Professor positions to start in Fall 2026. We are looking for candidates with expertise in artificial intelligence (AI), specifically in AI-driven cybersecurity or cyber operations, or expertise in trustworthiness, explainability, or fairness in AI.

The University of Arizona is a Research 1 institution (very high research spending and doctorate production) and the College of Information Science supports seven undergraduate degrees and five graduate degrees, including the #3 ranked Cybsersecurity MS, the #4 ranked Data Science MS and the #24 ranked Library and Information Science MA.

Qualifications: * Ph.D. in information science, computer science, computer engineering, cybersecurity or a related field, completed before start date * A strong publication record in respected venues in artificial intelligence and a research agenda with promising future research directions * Expertise in AI-driven cybersecurity or cyber operations; OR expertise in trustworthiness, explainability, or fairness in AI

Apply by December 15, 2025

Remote - Americas

Machine Learning Engineer - Ads

Great advertising connects merchants with customers who genuinely need what they're selling. As a Machine Learning Engineer focused on Ads, you'll build the targeting and personalization technology that makes these meaningful connections happen at scale. You'll develop sophisticated machine learning models that help merchants reach the right audience at exactly the right moment, creating advertising experiences that drive real business growth while respecting the customer experience.



Key Responsibilities:

• Develop and optimize advanced machine learning models for ad targeting and personalization systems
• Analyze comprehensive ad performance data to identify optimization opportunities and maximize ad spend efficiency
• Collaborate closely with advertising teams to integrate ML solutions seamlessly into our ad platform
• Research and implement innovative algorithms and tools to enhance ad relevance and effectiveness
• Document technical insights and share best practices across engineering teams

Qualifications:

• Extensive experience building and deploying machine learning models for advertising systems at scale
• Strong proficiency in ML frameworks including TensorFlow or PyTorch, with expert-level Python programming skills
• Proven analytical skills for processing and extracting insights from large-scale datasets
• Demonstrated problem-solving abilities and innovative thinking in ad technology solutions
• Solid familiarity with ad platforms, A/B testing methodologies, and data-driven decision making processes
• Experience with statistical methods and performance optimization for ML systems

Ready to connect merchants with their perfect customers? Join the team that's making commerce better for everyone.


At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.



This role may require on-call work

Faculty Positions in Electrical and Electronics Engineering – Koç University, Istanbul, Türkiye

Koç University invites exceptional candidates to apply for full-time faculty positions in Electrical and Electronics Engineering. We seek outstanding researchers in all areas of electrical and electronics engineering, including artificial intelligence, machine learning, computational neuroscience, intelligent systems, and signal processing.

Applicants should have a bold, interdisciplinary research vision capable of making transformative impacts across multiple domains. Successful candidates will leverage Koç University’s state-of-the-art research ecosystem, including the Koç University İş Bank Artificial Intelligence Research Center (KUIS AI), the Translational Medicine Research Center (KUTTAM), and the Nanofabrication and Nanocharacterization Center (n2STAR). KUIS AI provides a high-performance computation facility and scholarship support for KUIS AI graduate fellows, fostering close collaboration between faculty and students.

Koç University is a leading private, nonprofit institution in Istanbul, supported by the Vehbi Koç Foundation, with English as the medium of instruction. It hosts the highest number of ERC grant recipients in Türkiye and offers exceptional opportunities for interdisciplinary collaboration across engineering, medicine, and natural sciences. We offer competitive salaries, housing support, K–12 education assistance, private health insurance, and research startup funds.

We will be attending NeurIPS 2025 — interested candidates are welcome to reach out and schedule an informal discussion during the conference at alperdogan@ku.edu.tr.

Application materials: CV, research statement, teaching statement, and three references. Deadline: March 20, 2026 (applications reviewed on a rolling basis). Apply at: https://ee.ku.edu.tr/open-positions/faculty-positions/

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

Global: United States, Europe and Asia

At Citadel, our mission is to be the most successful investment team in the world. Quantitative Researchers play a key role in this mission by developing next-generation models and trading approaches for a range of investment strategies. You’ll get to challenge the impossible in quantitative research by applying sophisticated and complex statistical techniques to financial markets, some of the most complex data sets in the world. As an intern, you’ll get to challenge the impossible in research through an 11 week program that will allow you to collaborate and connect with senior team members. In addition, you’ll get the opportunity to network and socialize with peers throughout the internship. Our signature internship program takes place June through August. Occasionally, we can be flexible to other times of the year. You will be able to indicate your timing preference in the application.

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

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.