Location United States

Description At Oracle Cloud Infrastructure (OCI), we are building the future of cloud computing—designed for enterprises, engineered for performance, and optimized for AI at scale. We are a fast-paced, mission-driven team within one of the world’s largest cloud platforms. The Multimodal AI team in OCI Applied Science is working on developing cutting-edge AI solutions using Oracle's industry leading GPU-based AI clusters to disrupt industry verticals and push the state-of-the-art in Multimodal and Video GenAI research. You will work with a team of world-class scientists in exploring new frontiers of Generative AI and collaborate with cross-functional teams including software engineers and product managers to deploy these globally for real-world enterprise use-cases at the largest scale.

Responsibilities: - Contribute to the development and optimization of distributed multi-node training infrastructure - Stay Updated: Maintain a deep understanding of industry trends and advancements in video generatio, multimodal understanding, pretraining workflows and paradigms. -Model Development: Design, develop, and train state-of-the-art image and vide generation models that meet the highest quality standards. - Collaborate with cross-functional teams to support scalable and secure deployment pipelines. - Assist in diagnosing and resolving production issues, improving observability and reliability. - Write maintainable, well-tested code and contribute to documentation and design discussions

Minimum Qualifications - BS in Computer Science or related technical field. - 6+ years of experience in backend software development with cloud infrastructure. - Strong proficiency in at least one language such as Go, Java, Python, or C++. - Experience building and maintaining distributed services in a production environment. - Familiarity with Kubernetes, container orchestration, and CI/CD practices. - Solid understanding of computer science fundamentals such as algorithms, operating systems, and networking.

Preferred Qualifications - MS in Computer Science. - Experience in large-scale multi-node distributed training of LLMs and multimodal models. - Knowledge of cloud-native observability tools and scalable service design. - Interest in compiler or systems-level software design is a plus.

Why Join Us - Build mission-critical AI infrastructure with real-world impact. - Work closely with a collaborative and experienced global team. - Expand your knowledge in AI, cloud computing, and distributed systems. - Contribute to one of Oracle’s most innovative and fast-growing initiatives.

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: $96,800 to $223,400 per annum. May be eligible for bonus and equity.

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

Looking to study for a PhD?

I am looking for new students to join my ML group at the University of New South Wales, Sydney, Australia. The UNSW is ranked #19 in the QS Ranking 2025.

1. To succeed, you need an outstanding publication record, e.g., one or more first-author papers in NeurIPS, ICML, ICLR, CVPR, AAAI, ICCV, ECCV, IJCAI, SIG KDD, etc. You also need a high GPA from a very good uni (high in rankings). Patents, professional experience and non-first authors in the mix also help.

2. Topics include (non-exhaustively): (provable) machine UNlearning and model adaptation, MMLM and improving modality alignment, super-alignment, self-supervised physics-grounded models, safety in ML protein representations (also safety in general models), structured/technical diagrams understanding, structural diffusion models, next gen architectures beyond transformers, billion nodes/edges large scale graph learning.

3. Opportunities: CSC scholarships (due 16 Jan 2026) with uni. top-up, international scholarship rounds (due 17 April 2026), for exceptional candidates direct funding may be available (flex start)

Contact: Assoc. Prof. Piotr Koniusz: p.koniusz@unsw.edu.au See: www.koniusz.com (if you are attending NeurIPS, you can try reach me for an informal chat)

San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; Remote, US

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

With more than 600 million users around the world and 400 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

We are seeking talented Staff Machine Learning Engineers for multiple openings across our Core Engineering organization, including teams such as Search, Notifications, and Content & User Engineering. In these roles, you will drive the development of state-of-the-art applied machine learning systems that power core Pinterest experiences.

What you’ll do:

• Design features and build large-scale machine learning models to improve user ads action prediction with low latency
• Develop new techniques for inferring user interests from online and offline activity
• Mine text, visual, and user signals to better understand user intention
• Work with product and sales teams to design and implement new ad products

What we’re looking for:

• Degree in computer science, machine learning, statistics, or related field
• 6+ years of industry experience building production machine learning systems at scale, data mining, search, recommendations, and/or natural language processing
• 2+ years of experience leading projects/teams
• Strong mathematical skills with knowledge of statistical methods
• Cross-functional collaborator and strong communicator

ABOUT OUR TEAM

We are a remote-first team that sits across Europe and North America and comes together once a month in-person for 3 days and for longer offsites twice a year.

Our R&D and production teams are a combination of more research and more engineering-oriented profiles, however, everyone deeply cares about the quality of the systems we build and has a strong underlying knowledge of software development. We believe that good engineering leads to faster development iterations, which allows us to compound our efforts.

ABOUT THE ROLE

You would be working on our data team focused on the quality of the datasets being delivered for training our models. This is a hands-on role where your #1 mission would be to improve the quality of the pretraining datasets by leveraging your previous experience, intuition and training experiments. This includes synthetic data generation and data mix optimization.

You would be closely collaborating with other teams like Pre-training, Fine-tuning and Product to define high-quality data both quantitatively and qualitatively.

Staying in sync with the latest research in the field of dataset design and pretraining is key for being successful in a role where you would be constantly showing original research initiatives with short time-bounded experiments and highly technical engineering competence while deploying your solutions in production. With the volumes of data to process being massive, you'll have at your disposal a performant distributed data pipeline together with a large GPU cluster.

YOUR MISSION

To deliver massive-scale datasets of natural language and source code with the highest quality for training poolside models.

RESPONSIBILITIES

• Follow the latest research related to LLMs and data quality in particular. Be familiar with the most relevant open-source datasets and models
• Closely work with other teams such as Pretraining, Fine-tuning or Product to ensure short feedback loops on the quality of the models delivered
• Suggest, conduct and analyze data ablations or training experiments that aim to improve the quality of the datasets generated via quantitative insights

SKILLS & EXPERIENCE

• Strong machine learning and engineering background
• Experience with Large Language Models (LLM)
• Good knowledge of Transformers is a must
• Knowledge/Experience with cutting-edge training tricks
• Knowledge/Experience of distributed training
• Trained LLMs from scratch
• Knowledge of deep learning fundamentals
• Experience in building trillion-scale pretraining datasets, in particular: Ingest, filter and deduplicate large amounts of web and code data
• Familiar with concepts making SOTA pretraining datasets: multi-linguality, curriculum learning, data augmentation, data packing, etc
• Run data ablations, tokenization and data-mixture experiments
• Develop prompt engineering pipelines to generate synthetic data at scale
• Fine-tuning small models for data filtering purposes
• Experience working with large-scale GPU clusters and distributed data pipelines
• Strong obsession with data quality
• Research experience
• Author of scientific papers on any of the topics: applied deep learning, LLMs, source code generation, etc, is a nice to have Can freely discuss the latest papers and descend to fine details
• Programming experience: strong algorithmic skills, Linux Git, Docker, k8s, cloud managed services, Data pipelines and queues, Python with PyTorch or Jax Nice to have:
• Prior experience in non-ML programming, especially not in Python
• C/C++, CUDA, Triton

BENEFITS

• Fully remote work & flexible hours
• 37 days/year of vacation & holidays
• Health insurance allowance for you and dependents
• Company-provided equipment
• Wellbeing, always-be-learning and home office allowances
• Frequent team get togethers
• Great diverse & inclusive people-first culture

AI Platform Engineer

Location: Boston (US) / Barcelona (Spain)

Position Overview

As an AI Platform Engineer, you are the bridge between AI research and production software. You will:

• Build and maintain AI infrastructure: model serving, vector databases, embedding pipelines
• Enable AI developers to deploy their work reproducibly and safely
• Design APIs for AI inference, prompt management, and evaluation
• Implement MLOps pipelines: versioning, monitoring, logging, experimentation tracking
• Optimize performance: latency, cost, throughput, reliability
• Collaborate with backend engineers to integrate AI capabilities into the product

Key Responsibilities

AI Infrastructure

• Deploy and serve LLMs (OpenAI, Anthropic, HuggingFace, fine-tuned models)
• Optimize inference latency and costs
• Implement caching, rate limiting, and retry strategies

MLOps & Pipelines

• Version models, prompts, datasets, and evaluation results
• Implement experiment tracking (Weights & Biases)
• Build CI/CD pipelines for model deployment
• Monitor model performance and drift
• Set up logging and observability for AI services

API Development

• Design and implement APIs (FastAPI)
• Create endpoints for prompt testing, model selection, and evaluation
• Integrate AI services with backend application
• Ensure API reliability, security, and performance

Collaboration & Enablement

• Work with AI Developers to productionize their experiments regarding improving user workflows
• Define workflows: notebook/test repository → PR → staging → production
• Document AI infrastructure and best practices
• Review code and mentor AI developers on software practices

Required Skills & Experience

Must-Have

• 7+ years of software engineering experience (Python preferred)
• Experience with LLMs and AI/ML in production: OpenAI API, HuggingFace, LangChain, or similar
• Understanding of vector databases (Pinecone, Chroma, Weaviate, FAISS)
• Cloud infrastructure experience: GCP (Vertex AI preferred) or AWS (SageMaker)
• API development: FastAPI, REST, async programming
• CI/CD and DevOps: Docker, Terraform, GitHub Actions
• Monitoring and observability
• Problem-solving mindset: comfortable debugging complex distributed systems
• Operating experience with AI deployment in enterprise environment

Nice-to-Have

• Experience fine-tuning or training models
• Familiarity with LangChain, Pydantic AI or similar frameworks
• Knowledge of prompt engineering and evaluation techniques
• Experience with real-time inference and streaming responses
• Background in data engineering or ML engineering
• Understanding of RAG architectures
• Contributions to open-source AI/ML projects

Tech Stack

Current Stack:

• Languages: Python (primary), Bash
• AI/ML: OpenAI API, Anthropic, HuggingFace, LangChain, Pydantic AI
• Vector DBs: Pinecone, Chroma, Weaviate, or FAISS
• Backend: FastAPI, SQLAlchemy, Pydantic
• Cloud: GCP (Vertex AI, Cloud Run), Terraform
• CI/CD: GitHub Actions
• Experiment Tracking: MLflow, Weights & Biases, or custom
• Containers: Docker, Kubernetes (optional)

What we offer:

Competitive compensation

Stock Options Plan: Empowering you to share in our success and growth.
Cutting-Edge Tools: Access to state-of-the-art tools and collaborative opportunities with leading experts in artificial intelligence, physics, hardware and electronic design automation.
Work-Life Balance: Flexible work arrangements in one of our offices with potential options for remote work.
Professional Growth: Opportunities to attend industry conferences, present research findings, and engage with the global AI research community.
Impact-Driven Culture: Join a passionate team focused on solving some of the most challenging problems at the intersection of AI and hardware.

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

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

San Francisco

WRITER is looking for an AI engineer with a strong software engineering background to join our expanding team of AI experts.

At WRITER, we believe in using the power of AI to unlock the potential of the enterprise. With the help of our AI engineers, we can continue to build the most advanced language model available in the industry and revolutionize how companies interact with AI. We’re looking for a creative problem solver who has a deep understanding of NLP and ML technologies and who can help us create powerful and meaningful applications of AI.

As an AI engineer at WRITER, you'll play a pivotal role in developing and implementing state-of-the-art generative AI models and algorithms. Collaborating closely with our diverse and dynamic team of software engineers, data scientists, and researchers, you'll be able to design and deploy AI solutions that drive our innovative products.

If you’re passionate about using AI to transform the enterprise, we want to hear from you.

Your responsibilities

• Collaborate closely with our broader engineering team, data scientists, and AI engineers to evolve our software architecture as we productize new AI-powered capabilities
• Evaluate the performance of AI models & systems through rigorous testing and experimentation.
• Deploy LLM-based applications in production, evaluating and improving their performance over time
• Collaborate with our skilled software engineers to seamlessly integrate AI-powered capabilities into production systems, ensuring scalability and efficiency.
• Stay up-to-date with the latest advancements in AI and machine learning research, and proactively suggest improvements to enhance our generative AI capabilities.
• Collaborate closely with cross-functional teams to understand business requirements and translate them into innovative AI solutions.
• Own the design, implementation, and maintenance of robust and scalable production retrieval and agentic systems
• Implement strong testing and CI/CD practices that help us move with confidence in our AI system development

Is this you?

• Bachelor’s degree in Computer Science, Engineering, Mathematics, related field, or equivalent experience
• High level of coding proficiency using Python
• 5+ years of professional experience in software engineering, AI/ML development including:
• Proficiency with production software (Python) and systems design
• Machine learning algorithms and model development techniques
• ML lifecycle tools like MLflow, dvc, weights & biases
• Cloud deployment of ML systems
• Professional experience with LLMs and large-scale models
• Very strong software engineering skills with a track record of building scalable, distributed product machine learning systems
• Strong analytical and problem-solving skills
• Ability to communicate complex ideas and concepts effectively
• Ability to work independently and collaboratively

Palo Alto, CA

Position Description: Video generation models have made significant progress recently but continue to struggle with respecting physics, causality, and fine controllability. At Tesla, we’re training world models on millions of hours of real-world action-conditioned video using one of the biggest compute clusters. Instead of generating more AI slop, our goal is to faithfully reproduce real-world successes and failures, on both the bot and car platform, for the purposes of evaluation and closed-loop reinforcement learning.

Responsibilities: Design and train action-conditioned video generation models that predict future frames and sensor states Develop causal, physics-aware architectures that model interactions, motion, and environmental dynamics Integrate 3D generative techniques such as Gaussian Splatting and volumetric rendering for high-fidelity realism Implement closed-loop training systems where models iteratively refine predictions through feedback and simulation Optimize distributed pipelines for large-scale multimodal training and real-time inference Collaborate across Autonomy and Robotics to align model design, evaluation, and deployment

Requirements: Expertise in generative video or world model architectures Strong background in spatiotemporal modeling, 3D scene understanding, or neural simulation Proficiency with PyTorch or JAX Experience in large-scale distributed training, especially the different forms of parallelism Familiarity with reinforcement or imitation learning in simulated or embodied environments Curiosity about building intelligent systems that understand and generate the world around them

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.