Location USA, WA, Seattle USA, NY, New York USA, CA, Palo Alto

Description The Sponsored Products and Brands (SPB) team at Amazon Ads is reimagining the advertising landscape through generative AI, revolutionizing how millions of customers discover products and engage with brands on Amazon and beyond. We are at the forefront of redefining advertising experiences—bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle, from ad creation and optimization to performance measurement and customer insights.

We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance advertiser needs, enhance the shopping experience, and strengthen the Amazon marketplace. If you are energized by solving complex challenges and pushing the boundaries of what’s possible with AI, join us in shaping the future of advertising.

The Department of Materials Science and Engineering (DMSE) together with the Schwarzman College of Computing (SCC) at Massachusetts Institute of Technology (MIT) in Cambridge, MA, seeks candidates at the level of tenure-track Assistant Professor to begin July 1, 2026 or on a mutually agreed date thereafter.

Materials engineering has always benefitted from theoretical and computational approaches to unveil relationships between structure, properties, processing, and performance. Recent advances in computing, including but not limited to artificial intelligence, are poised to dramatically advance the understanding and design of complex matter. DMSE and SCC jointly seek candidates with experience and interest in combining fundamental scientific principles with algorithmic innovations to empower discovery, understanding, and synthesis of materials with applications across critical societal domains --- healthcare, manufacturing, energy, sustainability, climate, and next-generation computing. This search encompasses all materials classes and scales, and is open to candidates with industry and start-up experience. Candidates are expected to develop research programs that target innovation in computational approaches well-suited to materials science and engineering research.

The successful candidate will have a shared appointment in both the Department of Materials Science and Engineering and SCC in either the Department of Electrical Engineering and Computer Science (EECS) or the Institute for Data, Systems, and Society (IDSS), depending on best fit.

Faculty duties include teaching at the undergraduate and graduate levels, advising students, conducting original scholarly research, and developing course materials at the graduate and undergraduate levels. Candidates are expected to teach in both the Department of Materials Science and Engineering and in the educational programs of SCC. The normal teaching load is two subjects per year.

Candidates should hold a Ph.D. in Materials Science and Engineering, Computer Science, Physics, Chemical Engineering, Chemistry, Applied Mathematics, or a related field. A PhD is required by the start of employment. The pay range for a 9-month academic appointment at the entry-level Assistant Professor rank (excluding summer salary): $140,000 - $150,000. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the individual's work experience and education/training, internal peer equity, and applicable legal requirements. These factors impact where an individual's pay falls within a range. Employment is contingent upon the completion of a satisfactory background check, including verifying any finding of misconduct (or pending investigation) from prior employers.

Applications should include: (a) curriculum vitae, (b) research statement, (c) a teaching and mentoring plan. Each candidate should also include the names and contact information of 3 reference letter writers, who should upload their letters of recommendation by November 30, 2025.

Please submit online applications to https://faculty-searches.mit.edu/dmse_scc/register.tcl. To receive full consideration, completed applications must be submitted by November 30, 2025.

MIT is an equal opportunity employer. We value diversity and strongly encourage applications from individuals from all identities and backgrounds. All qualified applicants will receive equitable consideration for employment based on their experience and qualifications and will not be discriminated against on the basis of race, color, sex, sexual orientation, gender identity, pregnancy, religion, disability, age, genetic information, veteran status, or national or ethnic origin. See MIT's full policy on nondiscrimination. Know your rights.

Work Location:

Toronto, Ontario, Canada

Description

We are currently seeking talented individuals for a variety of positions, ranging from junior to senior levels, and will evaluate your application in its entirety.

Layer 6 is the AI research centre of excellence for TD Bank Group. We develop and deploy industry-leading machine learning systems that impact the lives of over 27 million customers, helping more people achieve their financial goals and needs. Our research broadly spans the field of machine learning with areas such as deep learning and generative AI, time series forecasting and responsible use of AI. We have access to massive financial datasets and actively collaborate with world renowned academic faculty.

We are always looking for people driven to be at the cutting edge of machine learning in research, engineering, and impactful applications.

As a Research Machine Learning Scientist, you will

• Join a world-class team of machine learning researchers with an extensive track record in both academia and industry.

• Research, develop, and apply new techniques in deep learning to advance our industry leading products.

• Work with large-scale, real-world datasets that range from banking transactions, to large document collections.

• Collaborate closely with our engineering team in a fast-paced startup environment and see your research deployed in production with very short turnaround.

Required Qualifications:

• PhD or Master’s degree in Computer Science, Statistics, Mathematics, Engineering or a related field

• Strong background in machine learning and deep learning

• 2+ years of research experience with publication record

• Proven track record of applying machine learning to solve real-world problems

Preferred Qualifications:

• Depth of experience in relevant ML research disciplines

• Hands on experience in software systems development

• Experience with one or more of Pytorch, Tensorflow, Jax, or comparable library

• Experience with Spark, SQL, or comparable database systems

• Experience using GPUs for accelerated deep learning training

• Familiarity with cloud computing systems like Azure or AWS

Senior Software Engineer (Frontend, UX)

Location: Boston (US) / Barcelona (Spain)

About us:

Axiomatic_AI is dedicated to accelerating R&D by developing the next generation of Automated Interpretable Reasoning, a verifiably truthful AI model built for reasoning in science and engineering, empowering engineers specifically in hardware design and Electronic Design Automation (EDA), with a mission to revolutionize the fields of hardware design and simulation in the photonics and semiconductor industry. We seek highly motivated professionals to help us bring these innovations to life, driving the evolution from development to commercial product.

Position Overview

As a Senior Software Engineer focusing on Frontend at Axiomatic, you will:

• Own the entire product interface: design, implement, and maintain our web applications.
• Define UX/UI patterns for AI-assisted workflows focused on scientific workflows (chat interfaces, data visualizations).
• Collaborate closely with backend and AI teams to integrate complex functionality seamlessly.
• Establish frontend standards: component libraries, design systems, testing practices.
• Mentor mid engineers as the team grows.
• Balance beautiful design with technical performance (fast load times, responsive UI, accessibility).

Key Responsibilities

Product Development

• Build and maintain our web application (React Next.js, TypeScript).
• Design intuitive UX flows for AI-powered features (prompt editing, model selection, result visualization).
• Implement responsive, accessible, and performant UI components.
• Integrate with backend APIs (FastAPI, REST, WebSockets, SSE).
• Work closely with Product Owner to translate requirements into UI.

UX/UI Design

• Create wireframes, mockups, and prototypes for new features.
• Establish and maintain design system and component library.
• Conduct user testing and iterate based on feedback.
• Ensure consistency across the product.
• Design for technical users (researchers, engineers, data scientists).

Frontend Ownership

• Define frontend architecture and best practices.
• Ensure best practices are applied by the team.
• Set up testing strategy (unit, integration, smoke, e2e tests).
• Optimize performance (lazy loading, caching, bundle size).
• Review code and mentor team members.
• Contribute to technical roadmap and planning.

Collaboration

• Work with Backend/Tech Lead on API design.
• Collaborate with Product Owner on feature prioritization.
• Present demos and gather feedback from stakeholders.

Required Skills & Experience

Must-Have

• 7+ years of frontend development experience.
• Expert in modern JavaScript/TypeScript and React (Next.js).
• Strong UX/UI design skills: wireframing, prototyping, design systems.
• Understanding of web performance optimization and SEO.
• Proficiency with CSS (SCSS, Tailwind, etc.).
• Experience with state management (Redux, RxJS, etc.).
• Collaboration and communication skills.
• Fluent in English (Spanish is a plus).
• Knowledge of WebSockets and real-time communication.

Nice-to-Have

• Experience building AI-powered UIs (CopilotKit) chat interfaces, code editors, notebook-style interfaces).
• Background in scientific or technical product UX.
• Figma or similar design tool proficiency.
• Understanding of backend APIs (REST, GraphQL).

Tech Stack

Current Stack:

• Frontend: React (Next.js), TypeScript
• Styling: SCSS / Tailwind
• State Management: RxJS / Redux
• Backend APIs: FastAPI (Python), REST, WebSockets
• Testing: Jest, Cypress, Playwright
• Design: Figma
• Infrastructure: GCP, Cloud Run, CI/CD via GitHub Actions

San Francisco

We are seeking a talented software engineer with generative AI experience who is deeply proficient with python and typescript to join our dynamic and growing team at Writer. As a key member of our engineering team, you will play a crucial role in building the genAI software. Your primary focus will be on developing a state-of-the-art platform that harnesses generative AI technologies and you will deliver seamless and scalable solutions. You will work closely with cross-functional teams to design, implement, and maintain features that enhance the user experience, drive product growth, establish best practices, and integrate cutting-edge AI capabilities.

Your responsibilities

• Design and develop robust and scalable generative AI services using Python and open source frameworks such as Writer Agent Builder, LangChain, and n8n.
• Implement responsive and user-friendly frontend interfaces, leveraging technologies like React, TypeScript, and modern web frameworks.
• Work with cloud platforms such as AWS, GCP, or Azure to deploy and scale applications.
• Develop and integrate high-performance, low-latency APIs for AI-driven features.
• Ensure code quality through testing, peer reviews, and continuous integration.
• Collaborate with the team to build, and maintain generative AI agents.
• Participate in architectural design discussions and promote engineering best practices.
• Continuously improve the application’s performance, scalability, and maintainability.

Is This You?

• 5+ years of experience in software engineering at expert level with Python
• Experience building web applications using FastAPI and Asyncio
• Experience building with generative AI applications in production environments.
• Expertise with microservices architecture and RESTful APIs.
• Solid understanding of database technologies such as PostgreSQL and vector databases as Elastic, Pinecone, Weaviate, or similar.
• Familiarity with cloud platforms (AWS, GCP, etc.) and containerized environments (Docker, Kubernetes).
• Familiarity with MCP, devtools, AI agents, or contributed to open source
• You are committed to writing clean, maintainable, and scalable code, following best practices in software development.
• You enjoy solving complex problems and continuously improving the performance and scalability of systems.
• You thrive in collaborative environments, working closely with cross-functional teams to build impactful features.
• Proven ability to help teams adopt technical best practices.

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

About Handshake AI Handshake is building the career network for the AI economy. Our three-sided marketplace connects 18 million students and alumni, 1,500+ academic institutions across the U.S. and Europe, and 1 million employers to power how the next generation explores careers, builds skills, and gets hired. Handshake AI is a human data labeling business that leverages the scale of the largest early career network. We work directly with the world’s leading AI research labs to build a new generation of human data products. From PhDs in physics to undergrads fluent in LLMs, Handshake AI is the trusted partner for domain-specific data and evaluation at scale. This is a unique opportunity to join a fast-growing team shaping the future of AI through better data, better tools, and better systems—for experts, by experts.

Now’s a great time to join Handshake. Here’s why: Leading the AI Career Revolution: Be part of the team redefining work in the AI economy for millions worldwide. Proven Market Demand: Deep employer partnerships across Fortune 500s and the world’s leading AI research labs. World-Class Team: Leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, just to name a few. Capitalized & Scaling: $3.5B valuation from top investors including Kleiner Perkins, True Ventures, Notable Capital, and more.

About the Role As a Staff Research Scientist, you will play a pivotal role in shaping the future of large language model (LLM) alignment by leading research and development at the intersection of data quality and post-training techniques such as RLHF, preference optimization, and reward modeling. You will operate at the forefront of model alignment, with a focus on ensuring the integrity, reliability, and strategic use of supervision data that drives post-training performance. You’ll set research direction, influence cross-functional data standards, and lead the development of scalable systems that diagnose and improve the data foundations of frontier AI.

You will: Lead high-impact research on data quality frameworks for post-training LLMs — including techniques for preference consistency, label reliability, annotator calibration, and dataset auditing. Design and implement systems for identifying noisy, low-value, or adversarial data points in human feedback and synthetic comparison datasets. Drive strategy for aligning data collection, curation, and filtering with post-training objectives such as helpfulness, harmlessness, and faithfulness. Collaborate cross-functionally with engineers, alignment researchers, and product leaders to translate research into production-ready pipelines for RLHF and DPO. Mentor and influence junior researchers and engineers working on data-centric evaluation, reward modeling, and benchmark creation. Author foundational tools and metrics that connect supervision data characteristics to downstream LLM behavior and evaluation performance. Publish and present research that advances the field of data quality in LLM post-training, contributing to academic and industry best practices.

Desired Capabilities PhD or equivalent experience in machine learning, NLP, or data-centric AI, with a track record of leadership in LLM post-training or data quality research. 5 years of academic or industry experience post-doc Deep expertise in RLHF, preference data pipelines, reward modeling, or evaluation systems. Demonstrated experience designing and scaling data quality infrastructure — from labeling frameworks and validation metrics to automated filtering and dataset optimization. Strong engineering proficiency in Python, PyTorch, and ecosystem tools for large-scale training and evaluation. A proven ability to define, lead, and execute complex research initiatives with clear business and technical impact. Strong communication and collaboration skills, with experience driving strategy across research, engineering, and product teams.

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.

The Chan Zuckerberg Institute for Advanced Biological Imaging (CZ Imaging Institute) is building the next generation of imaging technologies to transform our understanding of biology in health and disease. Over the next decade, we aim to create breakthrough systems — spanning hardware, software, probes, and computational tools — that will empower scientists worldwide.

As part of the Chan Zuckerberg Initiative’s Imaging Program, the CZ Imaging Institute (https://czii.org/) combines engineering, computation, and biology to tackle grand challenges in biological imaging. Our work is shared broadly with the global scientific community through open science, direct collaborations, and partnerships.

The CZ Imaging Institute will create breakthrough technologies — hardware, software, biological probes, data, and platforms — that will be made available to the scientific community and adopted worldwide through a combination of direct access to the institute, open sharing of advances, and commercial partnerships. Researchers will collaboratively develop breakthrough biological imaging systems centered around grand challenges that push the boundaries of what we can see and measure.

We are seeking a creative and motivated Data Scientist to develop and apply cutting-edge computational methods for complex imaging problems. This role is ideal for candidates with expertise in applied mathematics, computational science, or physics, combined with modern machine learning approaches. You will design algorithms, build scalable tools, and collaborate across disciplines to advance scientific discovery.

This position is on-site in Redwood City, CA.

What You'll Do - Develop and apply algorithms for solving inverse problems in imaging and related computational challenges. - Use optimization, applied mathematics, and physics-inspired modeling to extract insights from high-dimensional data. - Incorporate modern machine learning and deep learning techniques to improve reconstruction, denoising, and feature detection. - Build robust, scalable pipelines for large-scale biological datasets. - Collaborate with biologists, microscopists, and engineers to design solutions aligned with scientific goals. - Contribute to technical documentation, publications, and presentations.

What You'll Bring - M.S. or Ph.D. in Applied Mathematics, Computer Science, Physics, Engineering, or a related field. - 1 - 5 years of relevant experience. - Strong foundation in inverse problems, optimization, or computational modeling. - Experience in machine learning and deep learning (e.g., PyTorch, TensorFlow). - Proficiency in Python or C++, and familiarity with scientific computing libraries. - Strong analytical, problem-solving, and communication skills. - Experience with imaging data (e.g., cryo-EM, tomography, or related modalities). - Familiarity with convex optimization, variational methods, or numerical PDEs. - Knowledge of GPU computing and high-performance environments. - Track record of scientific publications or open-source contributions.