USA - Seattle

Job Overview

At Arm, our research shapes the future of energy-efficient AI. We build the foundations of tomorrow’s intelligent systems - from next-generation processors and accelerators to cutting-edge ML models and tools. As Research Scientist, you’ll be part of a global team pushing the boundaries of what’s possible at the intersection of AI, architecture, and scalable compute.

We’re looking for curious, collaborative researchers who want to turn deep technical insights into real-world impact. Whether you’re advancing algorithms for efficient learning, designing ML-friendly compute architectures, or experimenting with new model deployment paradigms - your work at Arm can influence billions of devices worldwide.

Responsibilities

Your contributions will vary depending on your expertise, but may include: Investigating novel approaches and applications in machine learning Exploring how to make machine learning models and workloads more scalable, portable, and power-efficient Developing proof-of-concepts, prototypes, or simulation environments to test research ideas Collaborating with teams across Arm to integrate research into products and platforms Publishing, presenting, or contributing to academic and industrial research communities Working with partners and ecosystem stakeholders on long-term innovation initiatives

Required Skills and Experience

Strong foundational experience in machine learning, computer science, electrical / computer engineering, or related field. Proficiency in programming languages such as Python, C/C++, or similar Experience designing, training, or analyzing machine learning models or systems Interest in research and long-term innovation beyond immediate product delivery

“Nice to Have” Skills and Experience

Up to date understanding of machine learning trends Contributions to open-source or peer-reviewed publications Exposure to deploying machine learning models on edge, devices, or mobile platforms Familiarity with machine learning model optimization or deployment Familiarity with Arm architecture

Postdoctoral Research Fellow

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

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

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

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

Responsibilities

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

Required Qualifications

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

Preferred Experience

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

Palo Alto, CA

Position Description: The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence through cutting-edge hardware innovation. Comprising brilliant engineers and visionaries, the team designs and develops advanced AI chips tailored to accelerate Tesla’s machine learning capabilities. Their work powers the neural networks behind Full Self-Driving (FSD), and Tesla humanoid robot, Optimus, pushing the boundaries of computational efficiency and performance. By creating custom silicon and optimized architectures, the team ensures Tesla remains a leader in AI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life.

Responsibilities: Design, development, and testing of hardware components and systems Work with cross-functional teams to integrate hardware with software and other systems Develop prototypes and proof-of-concepts Influence design decisions through data analysis, provide technical documentation and reports Provide technical documentation and reports

Requirements: Degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field Experience in one of the following areas: AI Accelerators, EDA tools, Physical Design, RTL, DFT, DV, or microarchitecture Strong understanding of hardware design principles and concepts Knowledge and experience with logic design and synthesis tools and techniques Experience with programming languages (e.g., C++, Python, Perl, Linux, MATLAB) Ability to work effectively in a team environment

New York, New York

WRITER is experiencing an incredible market moment as generative AI has taken the world by storm. We're looking for a cloud platform engineer to establish our cloud platform team, focusing on building and scaling our multi-cloud architecture across AWS, GCP and Azure regions. In this founding role, you'll architect and implement highly scalable systems that handle complex multi-tenant workloads while ensuring proper tenant isolation and security.

As a cloud platform engineer, you'll work closely with our development teams to build robust, automated solutions for environment buildout, tenant management, and cross-region capabilities. You'll design and implement systems that ensure proper tenant isolation while enabling efficient environment lifecycle management. This is a unique opportunity to establish our cloud platform team and have a direct impact on our platform's scalability and security, working with cutting-edge technologies and solving complex distributed systems challenges.

Your responsibilities:

• Establish and lead the cloud platform team
• Architect and implement multi-cloud infrastructure across AWS, GCP and Azure regions
• Design and build highly scalable, distributed systems for multi-tenant workloads
• Define and implement best practices for automated infrastructure across cloud providers
• Architect and implement tenant isolation mechanisms to ensure data security and compliance
• Create and manage environment lifecycle automation for dev/qa/demo environments
• Design and implement cross-region capabilities and active-active deployments
• Develop tenant migration and pod management solutions
• Collaborate with development teams to understand tenant requirements and constraints
• Implement infrastructure as code for region-level deployments
• Monitor and optimize tenant isolation and security
• Document tenant management processes and best practices
• Stay current with industry trends in multi-tenant architectures
• Participate in on-call rotation for critical platform services
• Contribute to technical decisions around tenant isolation and region management
• Mentor and grow the cloud platform team
• Implement and maintain deployment automation and CI/CD pipelines
• Design and optimize Kubernetes infrastructure for multi-tenant workloads
• Drive infrastructure cost optimization and efficiency

Is this you?

• Have 8+ years of experience in cloud platform engineering or related role (site reliability engineering)
• Have 3+ years of experience leading engineering teams
• Are passionate about building secure, scalable multi-tenant platforms
• Have extensive experience with cloud platforms (AWS, GCP, or Azure)
• Are proficient in infrastructure as code (Terraform, CloudFormation, etc.)
• Have deep experience with multi-tenant architectures and tenant isolation
• Can write clean, maintainable code in Python, Go, or similar languages
• Understand containerization and orchestration (Docker, Kubernetes)
• Have proven experience with cross-region deployments and active-active architectures
• Are comfortable working with multiple development teams
• Can communicate technical concepts clearly to both technical and non-technical audiences
• Take ownership of projects and drive them to completion
• Are excited about building automated infrastructure solutions
• Have a strong focus on security and tenant isolation
• Are comfortable with on-call responsibilities
• Have experience with agile development methodologies
• Have experience establishing new teams and best practices
• Can balance technical leadership with hands-on implementation
• Are excited about solving complex distributed systems challenges
• Have experience with multi-cloud architectures and hybrid deployments

Senior Software Engineer (Backend)

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 (Backend) at Axiomatic, you will:

• Design and build scalable backend services (FastAPI, FastMCP, Python)
• Own key features end-to-end: from API design to database schema to deployment
• Integrate AI capabilities (LLMs, Agents) into production systems
• Collaborate with frontend, AI, and infrastructure teams on architecture and delivery
• Ensure system reliability, performance, and security
• Mentor other engineers as the team grows

Key Responsibilities

Architecture & Design

• Contribute to system architecture and technical decisions
• Design for scalability, reliability, and security
• Propose and implement improvements to codebase and infrastructure
• Document technical designs and API contracts
• Ensure best practices are followed by the team

Backend Development

• Design and implement REST APIs using FastAPI
• Build scalable, maintainable, and testable services
• Design database schemas and optimize SQL queries (PostgreSQL)
• Integrate with external services (OpenAI, Anthropic)
• Optimize API performance, latency, and throughput

Quality & Testing

• Write comprehensive unit and integration tests
• Participate in code reviews (give and receive feedback)
• Debug and resolve production issues
• Maintain high code quality standards

Collaboration & Mentorship

• Work closely with Tech Lead on architecture and roadmap
• Partner with AI Platform Engineer on AI integrations
• Mentor mid-level engineers and share knowledge

Required Skills & Experience

Must-Have

• 7+ years of backend development experience
• Deep knowledge in Python, FastAPI
• Strong database skills: PostgreSQL, SQL, ORMs (SQLAlchemy)
• Experience designing REST APIs: best practices, versioning, documentation
• Cloud platform experience: GCP preferred (AWS, Azure acceptable)
• Testing mindset: unit tests, integration tests, TDD
• Version control & CI/CD: Git, GitHub Actions, Docker
• Strong problem-solving skills: debugging, performance optimization
• Fluent in English (Spanish is a plus)

Nice-to-Have

• Experience with FastMCP
• Familiarity with LangChain, Pydantic AI or similar frameworks
• Knowledge of async programming (asyncio, async/await)
• Familiarity with AI/ML APIs (OpenAI, HuggingFace, Vertex AI)
• Understanding of infrastructure as code (Terraform)
• Experience with microservices architecture

Tech Stack

Current Stack:

• Backend: Python, FastAPI, SQLAlchemy, Pydantic AI, Alembic
• Databases: PostgreSQL, Redis (caching)
• APIs: REST, WebSockets, SSE
• AI/ML: OpenAI API, Anthropic, Gemini
• Cloud: Google Cloud Platform (Cloud Run, Cloud SQL, GCS, VPCs, Bucket)
• Infrastructure: Terraform, Docker
• CI/CD: GitHub Actions, Terraform
• Testing: pytest, pytest-asyncio, pytest-cov

Various locations available

Adobe Firefly is redefining creativity by bringing the power of generative AI to millions of users worldwide. The Evaluation Systems team builds the ML foundation that ensures Firefly’s creations are safe, high-quality, and aligned with evolving human needs.

We are seeking a Machine Learning Engineer with a passion for vision and multimodal understanding to help us advance the frontier of evaluating generative content. You will design, train, and deploy models that assess the quality, aesthetics, and safety of images and videos generated by foundation models. Your work will directly shape how creators engage with AI responsibly and at scale.

This is an opportunity to work at the intersection of state-of-the-art research, large-scale data, and production systems, in a team that values human-in-the-loop learning and model alignment as core principles.

What You’ll Do - Model Development: Build and fine-tune models (e.g., ViTs, VLMs, multimodal encoders) to evaluate generative content across quality, safety, and user alignment dimensions. - Human-in-the-Loop Training: Leverage large-scale, noisy human feedback data to train robust evaluation and reward models. - Production Deployment: Ship models as real-time services that gate content and provide quality guardrails, continuously monitoring and improving their performance. - Collaboration: Partner with product, research, and engineering teams to integrate evaluation signals into Firefly products and new creative experiences. - Exploration: Stay on top of the latest ML research (e.g., diffusion models, alignment methods, multimodal evaluation) and translate advances into practical solutions.

What You Need to Succeed - MS or PhD in Computer Science, Statistics, Electrical Engineering, Applied Math, Operations Research, Econometrics or equivalent experience required - Strong understanding of machine learning and deep learning concepts, especially in vision and multimodal domains. - Experience with model training, finetuning, and evaluation. Proficiency in Python and familiarity with frameworks like PyTorch. Familiarity with large-scale data pipelines and distributed training is a plus. - Ability to translate research concepts into scalable, production-ready systems. Prior exposure to vision-language models or human feedback training is a plus. - Strong analytical and quantitative problem-solving ability. - Excellent communication, relationship skills and a strong team player.

New York / Chicago / Austin

You will develop, refine and implement algorithmic trading strategies that shape the future of electronic trading. Working alongside a research team of mathematicians, scientists and technologists, you will leverage vast data sets to construct complex models to predict market movements. With your expertise in statistics and exceptional analytical and research skills, you will develop innovative solutions that are foundational to Optiver’s trading strategies.

You will participate in Optiver’s Global Academy and be equipped with the knowledge needed to make an impact the moment you join your team. The comprehensive training covers trading theory and Optiver’s tech stack to hone your skills for your role. You will also be paired with a dedicated mentor who will empower you to take ownership of your work and make a difference.

As a Quantitative Researcher, you will have the opportunity to contribute to several key areas: • Using statistical models and machine learning to develop trading algorithms. • Leveraging big data technologies to analyze high-frequency trading strategies, market microstructure and financial instruments to identify trading opportunities. • Building stochastic models to determine the fair value of financial derivatives. • Combining quantitative analysis and high-performance implementation to ensure the efficiency and accuracy of pricing engines and libraries.

You’ll join a culture of collaboration and excellence, where you’ll be surrounded by curious thinkers and creative problem solvers. Motivated by a passion for continuous improvement, you’ll thrive in a supportive, high-performing environment alongside talented colleagues, working collectively to tackle the toughest problems in the financial markets. In addition, you’ll receive: • A performance-based bonus structure unmatched anywhere in the industry. We combine our profits across desks, teams and offices into a global profit pool. • The opportunity to work alongside best-in-class professionals from over 40 different countries. • Ownership over initiatives that directly solve business problems. • 401(k) match up to 50% and fully paid health insurance. • 25 paid vacation days alongside market holidays. • Extensive office perks, including breakfast, lunch and snacks, regular social events, clubs, sporting leagues and more.

Who you are: • PhD in Mathematics, Statistics, Computer Science, Physics, or a related STEM field, with outstanding academic achievements • Expected to graduate by mid-2026 and available to start full-time employment upon graduation • Solid foundation in mathematics, probability, and statistics • Excellent research, analytical, and modeling skills • Independent research experience • Proficiency in any programming language • Experience in machine learning, with practical applications in time-series analysis and pattern recognition • Strong interest in working in a fast-paced, collaborative environment • Fluent in English with strong written and verbal communication skills

At Optiver, our mission is to improve the market by injecting liquidity, providing accurate pricing, increasing transparency and stabilising the market no matter the conditions. With a focus on continuous improvement, we prioritise safeguarding the health and efficiency of the markets for all participants. As one of the largest market making institutions, we are a respected partner on 100+ exchanges across the globe. Our differences are our edge. Optiver does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, or other legally protected characteristics.

Optiver is supportive of US immigration sponsorship for this role.

*We accept one application per role per year. If you have previously applied to this position during this season and have been unsuccessful, you can reapply once the next recruitment season begins in 2026.

Rochester, Minnesota, USA

Mayo Clinic seeks a highly motivated individual to advance the development, validation, and real-world implementation of generative AI systems for clinical decision support in Gastroenterology and Hepatology. This role bridges research and translation into clinical workflows, focusing on building trustworthy AI systems that augment human presence and put the needs of the patient first. Research Fellows will work within a multidisciplinary team of data scientists, physicians, and engineers to design novel generative agentic architectures, develop useful benchmarks, and work together with clinical teams to decrease time to diagnosis and time to treatment. Contact shung.dennis@mayo.edu if interested.

Chicago / Austin

As a Quantitative Research Intern, you will work side-by-side with our Research Team of mathematicians, scientists and technologists, to develop and enhance the models that drive Optiver’s trading. You will tackle a practical research project that has real-world impact and directly influences Optiver’s trading decisions. In our business, where the markets are always evolving, you will use your skills to predict its movements.

What you’ll do: Led by our in-house education team, you will delve into trading fundamentals and engage in a research project that makes a real-world impact. You will be paired with one of Optiver’s seasoned researchers, providing you exposure to a variety of research areas, including: • Using statistical models and machine learning to develop trading algorithms. • Leveraging big data technologies to analyze high-frequency trading strategies, market microstructure, and financial instruments to identify trading opportunities. • Building stochastic models to determine the fair value of financial derivatives. • Combining quantitative analysis and high-performance implementation to ensure the efficiency and accuracy of pricing engines and libraries.

What you’ll get: You’ll join a culture of collaboration and excellence, surrounded by curious thinkers and creative problem-solvers. Motivated by a passion for continuous improvement, you’ll thrive in a supportive, high-performing environment alongside talented colleagues, collectively tackling some of the toughest challenges in the financial markets.

In addition, you’ll receive: • The opportunity to work alongside best-in-class professionals from over 40 different countries • The opportunity to earn a return internship or full-time offer in Chicago, Austin, New York City, or Amsterdam based on performance • A highly-competitive internship compensation package • Optiver-covered flights, living accommodations, and commuting stipends • Extensive office perks, including breakfast, lunch and snacks, regular social events, clubs, sporting leagues and more

Who you are: • Currently enrolled in a PhD program in Mathematics, Statistics, Computer Science, Physics or a related STEM field with outstanding academic performance • Expected graduation between December 2026 and June 2028 • Available to intern during Summer 2026 • Open to full-time opportunities upon graduation in 2027 or 2028 • Solid foundation in mathematics, probability, and statistics • Excellent research, analytical, and modeling skills • Independent research experience • Proficiency in any programming language • Experience in machine learning, with practical applications in time-series analysis and pattern recognition • Strong interest in working in a fast-paced, collaborative environment • Fluent in English with strong written and verbal communication skills

Who we are: At Optiver, our mission is to improve the market by injecting liquidity, providing accurate pricing, increasing transparency and stabilising the market no matter the conditions. With a focus on continuous improvement, we prioritise safeguarding the health and efficiency of the markets for all participants. As one of the largest market making institutions, we are a respected partner on 100+ exchanges across the globe. Our differences are our edge. Optiver does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, or other legally protected characteristics.

Optiver is supportive of US immigration sponsorship for this role.

*We accept one application per role per year. If you have previously applied to this position during this season and have been unsuccessful, you can reapply once the next recruitment season begins in 2026.

Palo Alto, CA

Position Description: As a Software Engineer for the Optimus team, you will build the tools and infrastructure to make and measure improvements to neural network architecture, visualize data, assist with exporting and deploying neural networks to the bot, and evaluate experimental results. You will help us automate the entire workflows of training, validation, and production of the Optimus. Most importantly, you will see your work repeatedly shipped to and utilized by thousands of Humanoid Robots in real world applications.

Responsibilities: Build and improve our Python training infrastructure for stable and faster training

Build the tooling and infrastructure for reporting and visualizing model metrics and performance

Build the pipelines to run and validate our PyTorch models

Manage, analyze, and visualize our training and test datasets

Coordinate with the team managing the hardware cluster to maintain high availability / jobs throughput for Machine Learning

Build and improve tooling to deploy trained neural nets to Tesla hardware

Requirements: Practical experience programming in Python and/or C++

Proficient in system-level software, particularly hardware-software interactions and resource utilization

Understanding of modern machine learning concepts and state of the art deep learning

Experience working with training frameworks, ideally PyTorch

Demonstrated experience scaling neural network training jobs across clusters of GPU’s

Optional: Previous experience in deep learning deployment

Optional: Profiling and optimizing CPU-GPU interactions (pipelining compute/transfers, etc)