You will play an active part in shaping product features based on what's technically possible. Furthermore, you will make sure our company hits our ambitious goals from an engineering standpoint.

You bring a passion for meeting business needs while building technically innovative solutions, and excel at shifting between the two,understanding how big-picture goals inform technical details, and vice-versa.

You thrive in a fast-paced iterative engineering environment.

Examples of desirable skills, knowledge and experience:

• A minimum of 3 years experience in software development, with a strong focus on JavaScript, TypeScript and React;
• Bachelor's degree in Computer Science, Engineering, or a related field;
• Experience with frontend frameworks and tooling;
• Good understanding of HTML, CSS and how to work with product design teams;
• Good understanding of how browsers work and their underlying technologies;
• Solid understanding of systems engineering principles and best practices;
• Experience with version control systems such as Git;
• Strong problem-solving skills and attention to detail;
• Excellent communication and interpersonal skills, with the ability to work effectively in a team environment;
• Passion for learning and exploring new technologies;
• Creative thinker with the ability to propose innovative solutions to complex problems;
• An operational mindset - we don't just write code, we also own it in production;

Bonus Points:

• Previous experience working in an Agile environment;
• Experience building high performance distributed systems;
• Understanding of the web and its underlying protocol stack, such as HTTP;
• Familiar with AI, AI agents, and related technologies and standards;
• Contributions to large open source projects.

This role may require flexibility to be on-call outside of standard working hours to address technical issues as needed.

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As a full stack software engineer in Anduril Labs, you will help bring innovative, next-generation concepts to life through proof-of-concept development and rapid prototyping using bleeding edge technologies.

The ideal candidate has exceptional software development and creative problem-solving skills, is a self-starter, and can quickly grasp complex concepts.

As a full stack software engineer, you possess the skills to architect, develop, and deploy distributed applications and services, including both front-end and back-end components.

You have experience with agile, end-to-end software development lifecycle and are comfortable developing and deploying code across Windows and Linux-based systems (including standalone bare-metal hardware, virtualized environments, and cloud-hosted platforms).

Embedded software development experience is a plus.

You are also proficient in integrating legacy code and systems, leveraging open-source technologies, and developing and utilizing APIs.

Additionally, you have a solid understanding of AI/ML core concepts (e.g., feature extraction, supervised vs. unsupervised learning, regression, classification, clustering, deep learning neural networks, NLP, LLMs, SLMs, model fine-tuning, prompt engineering, RAG) and hands-on experience developing (Gen)AI-enhanced applications or services.

We also expect candidates to have familiarity with database technologies (e.g., SQL, NoSQL, Graph DB, Vector DB) and experience with data modeling, data wrangling, analytics, and visualization.

Since Anduril Labs supports all Anduril businesses and product lines, you will have the unique opportunity to work closely with multi-disciplinary engineering and product development teams across the entire company.

This means you will get to directly contribute to the development of Anduril’s next-generation products and services.

So if you thrive in a dynamic environment that values creative problem-solving, love writing code, excel as both an individual contributor and team player, are eager to learn, and bring a can-do attitude, this role is for you.

Key Responsibilities:

• Lead the development of prototypes to demonstrate advanced concepts in areas like autonomous and multi-agent systems, GenAI, advanced data analytics, quantum computing/sensing/networking/comms/machine learning, modeling, simulation, optimization, visualization, next-gen human-machine interfaces, heterogenous computing, and cybersecurity.

• Own the entire Software Development Lifecycle from inception through development, testing, deployment, and documentation for Anduril Labs-developed software prototypes.

• Interface and collaborate with other Anduril and customer engineering teams, and strategic partners.

• Support Anduril- and customer-funded R&D efforts.

• Participate in field experiments and technology demonstrations.

Requirements:

• 3+ years of programming with Python, C++, Java, Rust, Go, or JavaScript/TypeScript.

• Proven software architecture and design skills.

• Ability to quickly understand and navigate complex systems and established codebases.

• AI/ML development using commercial and open-source AI frameworks, models, and tools (e.g., Jupyter Notebook, PyTorch, TensorFlow, Scikit-learn, OpenAI, Claude, Gemini, Llama, LangChain, YOLO, AWS Sagemaker, Bedrock, Azure AI, RAG).

• Web app development (e.g., React, Angular, or Vue).

• Cloud development (e.g., AWS, Azure, or GCP).

• Data modeling and wrangling.

• Networking basics (e.g., DNS, TCP/IP vs. UDP, socket communications, LDAP, Active Directory).

• Database technologies (e.g., SQL, NoSQL, Graph DB, Vector DB).

• API development and integration (e.g., REST, GraphQL).

• Containerization technologies (e.g., Docker, Kubernetes).

• Software development on Linux and Windows.

• Demonstrable hands-on experience using GenAI tools (e.g., OpenAI Codex, Claude Code, Gemini Code Assist, GitHub Copilot, Amazon CodeWhisperer, or similar) for software development, code generation, debugging, and algorithmic exploration.

• Experience with Git version control, build tools, and CI/CD pipelines.

• Demonstrated understanding and application of software testing principles and practices, including unit testing, integration testing, and end-to-end testing.

• Strong problem-solving skills, meticulous attention to detail, and the ability to work effectively in a collaborative team environment.

• Excellent communication and interpersonal skills, with the ability to effectively articulate complex technical concepts to diverse audiences.

• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance.

Preferred Qualifications:

• BS in Computer Science, Engineering, or similar field.

• Distributed applications development (e.g., client/server, microservices, multi-agent solutions).

• High performance computing (HPC) and big data technologies (e.g., Apache Spark, Hadoop).

• Mobile app development (e.g., iOS or Android).

• Embedded software development experience.

• Willingness to travel up to approximately 10% US

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At Cloudflare, we have our eyes set on an ambitious goal: to help build a better Internet. Today the company runs one of the world's largest networks that powers trillions of requests per month. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code.

About the Department

Emerging Technologies & Incubation (ETI) is where new and bold products are built and released within Cloudflare. Rather than being constrained by the structures which make Cloudflare a massively successful business, we are able to leverage them to deliver entirely new tools and products to our customers.

About the Team

The Cloudflare Queues team delivers our managed global message queue service. Queues lets developers reliably send and receive messages, buffer or batch operations, and decouple load among services on the edge. It features message batching, automatic retries, and at-least once delivery guarantees. Queues is integrated with Cloudflare Workers; a Worker can send messages to a Queue, and consume messages from a Queue.

What you'll do

We are looking for an Engineering Manager to join our team. You will work with a team of passionate, talented engineers that are building innovative products that bring security and speed to millions of internet users each day. You will play an active part in shaping product features and improving performance to make Queues the best it can be. You will make sure our company hits our ambitious goals from an engineering standpoint. You will change the way people build applications. You bring a passion for meeting business needs by building technical, innovative solutions. You excel to understand how big-picture goals inform technical details. You thrive in a fast-paced iterative engineering environment and have experience in delivering scalable distributed systems. Most importantly, you have a track record of having past teams respect you as both a technical leader and manager.

Examples of desirable skills, knowledge and experience

• Strong communications skills - especially building a shared understanding of systems among a team's members.
• Comfortable leading and hiring a team that builds distributed systems.
• Navigate uncertainty and ambiguity - many of the things we build have never been built before anywhere and you are expected to find a way to deliver.
• Excel at planning, creating teams, and overseeing execution to meet commitments and deliver with predictability
• Comfortable building developer-loved APIs that scale
• Demonstrate a track record of leading a team including hiring, on-boarding, and professional development. You inspire your team to reach higher. You’re as good as explaining “why” as you are “how”.
• Experience implementing tools, process, internal instrumentation, methodologies and resolving blockages
• At least 4 years of recent professional experience with TypeScript or Go.
• Solid understanding of computer science fundamentals including data structures, algorithms, and object-oriented or functional design.
• Deep understanding of the web and technologies such as web browsers, HTTP, JavaScript and WebAssembly

Bonus Points

• Experience building high performance distributed systems.
• Experience working with cloud platforms, especially serverless platforms.
• Deep Linux/UNIX systems, kernel, or networking knowledge
• Contributions to large open source projects
• Experience working with async software patterns like queues, pub-sub, and event buses.
• Experience debugging, optimizing and identifying failure modes in a large-scale Linux-based distributed system.

Compensation

Compensation may be adjusted depending on work location.

• For New York City, New Jersey, Washington, Washington DC, and California (excluding Bay Area) based hires: Estimated annual salary of $170,000 - $260,000

Equity

This role is eligible to participate in Cloudflare’s equity plan.

Benefits

Cloudflare offers a complete package of benefits and programs to support you and your family. Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun! The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S.

• Health & Welfare Benefits
• Medical/Rx Insurance
• Dental Insurance
• Vision Insurance
• Flexible Spending Accounts
• Commuter Spending Accounts
• Fertility & Family Forming Benefits
• On-demand mental health support and Employee Assistance Program
• Global Travel

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At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies.

We protect and accelerate any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks.

Available Locations:

Austin, TX | Lisbon, Portugal | London, UK

About the Department

Emerging Technologies & Incubation (ETI) is where new and bold products are built and released within Cloudflare. Rather than being constrained by the structures which make Cloudflare a massively successful business, we are able to leverage them to deliver entirely new tools and products to our customers.

Cloudflare’s edge and network make it possible to solve problems at massive scale and efficiency which would be impossible for almost any other organization.

About the Team

The Workers Runtime team delivers features and improvements to our Runtime which actually executes customer code at the edge. We care deeply about increasing performance, improving JS API surface area and compiled language support through WebAssembly, and optimizing to meet the next 10x increase in scale.

The Runtime is a hostile environment - System resources such as memory, cpu, I/O, etc need to be managed extremely carefully and security must be foundational in everything we do.

What you'll do

We are looking for a Systems Engineer to join our team. You will work with a team of passionate, talented engineers that are building innovative products that bring security and speed to millions of internet users each day.

You will play an active part in shaping product features based on what’s technically possible. You will make sure our company hits our ambitious goals from an engineering standpoint.

You bring a passion for meeting business needs while building technically innovative solutions, and excel at shifting between the two,understanding how big-picture goals inform technical details, and vice-versa.

You thrive in a fast-paced iterative engineering environment.

Examples of desirable skills, knowledge and experience

• At least 2 years of recent professional experience with C++ or Rust.
• Solid understanding of computer science fundamentals including data structures, algorithms, and object-oriented or functional design.
• An operational mindset - we don't just write code, we also own it in production.
• Deep understanding of the web and technologies such as web browsers, HTTP, JavaScript and WebAssembly.
• Experience working in low-latency real time environments such as game streaming, game engine architecture, high frequency trading, payment systems.
• Experience debugging, optimizing and identifying failure modes in a large-scale Linux-based distributed system.

Bonus Points

• Experience building high performance distributed systems in Rust.
• Experience working with cloud platforms, especially server-less platforms.
• Experience with the internals of JS engines such as V8, SpiderMonkey, or JavaScriptCore.
• Experience with standalone WebAssembly runtimes such as Wasmtime, Wasmer, Lucet, etc.
• Deep Linux/UNIX systems, kernel, or networking knowledge.
• Contributions to large open source projects

What Makes Cloudflare Special?

We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.

Project Galileo: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.

Athenian Project: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states.

1.1.1.1: We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released.

Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers.

Sound like something you’d like to be a part of? We’d love to hear from you!

This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license.

Cloudflare is proud to be an equal opportunity employer. We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness. All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law.

We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.

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About the Role:

When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe.

Think of us as doing "neuroscience" of neural networks using "microscopes" we build - or reverse-engineering neural networks like binary programs.

More resources to learn about our work:

• Our research blog - covering advances including Monosemantic Features and Circuits

• An Introduction to Interpretability from our research lead, Chris Olah

• The Urgency of Interpretability from CEO Dario Amodei

• Engineering Challenges Scaling Interpretability - directly relevant to this role

• 60 Minutes segment - Around 8:07, see a demo of tooling our team built

• New Yorker article - what it's like to work on one of AI's hardest open problems

Even if you haven't worked on interpretability before, the infrastructure expertise is similar to what's needed across the lifecycle of a production language model:

• Pretraining: Training dictionary learning models looks a lot like model pretraining - creating stable, performant training jobs for massively parameterized models across thousands of chips

• Inference: Interp runs a customized inference stack. Day-to-day analysis requires services that allow editing a model's internal activations mid-forward-pass - for example, adding a "steering vector"

• Performance: Like all LLM work, we push up against the limits of hardware and software. Rather than squeezing the last 0.1%, we are focused on finding bottlenecks, fixing them and moving ahead given rapidly evolving research and safety mission

The science keeps scaling - and it's now applied directly in safety audits on frontier models, with real deadlines. As our research has matured, engineering and infrastructure have become a bottleneck. Your work will have a direct impact on one of the most important open problems in AI.

Responsibilities:

• Build and maintain the specialized inference and training infrastructure that powers interpretability research - including instrumented forward/backward passes, activation extraction, and steering vector application

• Resolve scaling and efficiency bottlenecks through profiling, optimization, and close collaboration with peer infrastructure teams

• Design tools, abstractions, and platforms that enable researchers to rapidly experiment without hitting engineering barriers

• Help bring interpretability research into production safety audits - with real deadlines and high reliability expectations

• Work across the stack - from model internals and accelerator-level optimization to user-facing research tooling

You may be a good fit if you:

• Have 5-10+ years of experience building software

• Are highly proficient in at least one programming language (e.g., Python, Rust, Go, Java) and productive with Python

• Are extremely curious about unfamiliar domains; can quickly learn and put that knowledge to work, e.g. diving into new layers of the stack to find bottlenecks

• Have a strong ability to prioritize the most impactful work and are comfortable operating with ambiguity and questioning assumptions

• Prefer fast-moving collaborative projects to extensive solo efforts

• Are curious about interpretability research and its role in AI safety (though no research experience is required!)

• Care about the societal impacts and ethics of your work

• Are comfortable working closely with researchers, translating research needs into engineering solutions.

Strong candidates may also have experience with:

• Optimizing the performance of large-scale distributed systems

• Language modeling fundamentals with transformers

• High Performance LLM optimization: memory management, compute efficiency, parallelism strategies, inference throughput optimization

• Working hands-on in a mainstream ML stack - PyTorch/CUDA on GPUs or JAX/XLA on TPUs

• Collaborating closely with researchers and building tooling to support research teams; or directly performed research with complex engineering challenges

Representative Projects:

• Building Garcon, a tool that allows researchers to easily instrument LLMs to extract internal activations

• Designing and optimizing a pipeline to efficiently collect petabytes of transformer activations and shuffle them

• Profiling and optimizing ML training jobs, including multi-GPU parallelism and memory optimization

• Building a steered inference system that applies targeted interventions to model internals at scale (conceptually similar to Golden Gate Claude but for safety research)

Role Specific Location Policy:

• This role is based in the San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis.

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role's On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary: $315,000-$560,000 USD

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You want to build the cutting-edge systems that train AI models like Claude. You're excited to work at the frontier of machine learning, implementing and improving advanced techniques to create ever more capable, reliable and steerable AI.

As an ML Systems Engineer on our Reinforcement Learning Engineering team, you'll be responsible for the critical algorithms and infrastructure that our researchers depend on to train models. Your work will directly enable breakthroughs in AI capabilities and safety.

You'll focus obsessively on improving the performance, robustness, and usability of these systems so our research can progress as quickly as possible.

Our finetuning researchers train our production Claude models, and internal research models, using RLHF and other related methods. Your job will be to build, maintain, and improve the algorithms and systems that these researchers use to train models.

You'll be responsible for improving the speed, reliability, and ease-of-use of these systems.

Strong candidates may also have experience with:

High performance, large scale distributed systems Large scale LLM training Python Implementing LLM finetuning algorithms, such as RLHF

Representative projects:

Profiling our reinforcement learning pipeline to find opportunities for improvement Building a system that regularly launches training jobs in a test environment so that we can quickly detect problems in the training pipeline Making changes to our finetuning systems so they work on new model architectures Building instrumentation to detect and eliminate Python GIL contention in our training code Diagnosing why training runs have started slowing down after some number of steps, and fixing it Implementing a stable, fast version of a new training algorithm proposed by a researcher

Deadline to apply: None. Applications will be reviewed on a rolling basis.

The annual compensation range for this role is $500,000-$850,000 USD.

Logistics:

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.

Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links,visit anthropic.com/careers directly for confirmed position openings.

How we're different:

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact , advancing our long-term goals of steerable, trustworthy AI , rather than work on smaller and more specific puzzles.

We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time.

As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process

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You'll be working on large-scale ML systems from the ground up, making safe, steerable, trustworthy systems. You'll be excited to write code when you understand the research context and more broadly why it's important.

Strong candidates may also have experience with high performance, large-scale ML systems, GPUs, Kubernetes, Pytorch, or OS internals, language modeling with transformers, reinforcement learning, and large-scale ETL.

Representative projects may include optimizing the throughput of a new attention mechanism, comparing the compute efficiency of two Transformer variants, making a Wikipedia dataset in a format models can easily consume, scaling a distributed training job to thousands of GPUs, writing a design doc for fault tolerance strategies, and creating an interactive visualization of attention between tokens in a language model.

The annual compensation range for this role is $350,000-$500,000 USD.

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As an Engineering Manager on Anthropic's performance and scaling teams, you will be responsible for ensuring the team is identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems.

Responsibilities:

• Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
• Become familiar with the team's technical stack enough to make targeted contributions as an individual contributor
• Manage day-to-day execution of the team's work
• Prioritize the team's work and manage projects in a highly dynamic, fast-paced environment
• Coach and support your reports in understanding, and pursuing, their professional growth
• Maintain a deep understanding of the team's technical work and its implications for AI safety

Requirements:

• 1+ years of management experience in a technical environment, particularly performance or distributed systems
• Background in machine learning, AI, or a similar related technical field
• Deeply interested in the potential transformative effects of advanced AI systems and committed to ensuring their safe development
• Excel at building strong relationships with stakeholders at all levels
• Quick learner, capable of understanding and contributing to discussions on complex technical topics
• Experience managing teams through periods of rapid growth and change

Nice to have:

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

Compensation:

The annual compensation range for this role is $425,000-$560,000 USD.

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Department: Administration

Job Description:

UnitedMasters is building a marketplace that connects artists, brands, and fans - empowering artists to earn and grow. UnitedMasters has taken the bold step of building a music distribution service that, radically, puts artists first - disrupting the legacy music business by letting up-and-coming artists distribute their music directly to fans through streaming services while maintaining ownership of their master recording rights and up to 100% of royalties.

Through the combination of UnitedMasters' music distribution platform and its deep ties to brands, UnitedMasters enables independent artists and change-makers to grow and earn unlike any other platform.

The UnitedMasters team is made up of musicians, marketers, engineers, and storytellers with backgrounds from YouTube, SoundCloud, Pandora, Facebook, Uber, Dropbox, Complex, VICE, and more. We work hand in hand with the award-winning creative teams that forge those innovative partnerships at Translation (our in-house creative advertising agency).

What's the Role

UnitedMasters is seeking a Vice President, Artist & Label Marketing to lead marketing strategy and execution across our exclusive artist roster and growing label services business. Some of our exclusive artists include BigXThaPlug, Brent Faiyaz, and FloyyMenor. This is a senior leadership role responsible for defining the marketing vision for artists and labels while building and leading a high-performing team.

This role blends long-term strategy with day-to-day execution. You will set the roadmap, lead major campaigns and releases, develop talent, and partner closely with artists, managers, and cross-functional teams to drive impact and results. This role sets the creative bar for UnitedMasters' artist and label marketing by defining what 'great' looks like across brand, storytelling, and campaign execution.

Responsibilities

• Own the marketing vision and execution for UnitedMasters' exclusive artist roster and label services business including BigXThaPlug, Brent Faiyaz, and FloyyMenor
• Set and uphold a high creative standard across all campaigns, ensuring each release reflects strong storytelling, cultural relevance, and artistic integrity
• Develop long-term strategies while balancing excellence and accountability in day-to-day execution
• Serve as a strategic thought partner to senior leadership on artist growth, brand positioning, and market opportunity

Drive Marketing Excellence Across Releases

• Oversee campaign strategy, release planning, and marketing execution across all exclusive artists
• Ensure excellence in operations including timelines, deliverables, and cross-functional coordination
• Build and manage project budgets in partnership with Finance and maintain accountability
• Partner with Creative, Digital, Commerce, A&R, Publicity, and Sync teams to ensure seamless execution
• Maintain campaign visibility and accountability through reporting, updates, and performance tracking

Lead, Build & Inspire a Team

• Lead and invest in growing a high-performing Artist & Label Marketing organization
• Mentor, and develop marketing talent
• Foster a culture of creativity, accountability, and high performance
• Promote collaboration without sacrificing individual ownership or excellence

Partner with Artists, Managers & External Stakeholders

• Serve as a senior marketing advisor to artists and their teams
• Present strategies clearly and persuasively to artists, managers, and partners
• Build trust-based relationships across the roster
• Engage in pitching and strategic conversations as needed

Collaborate Across the Enterprise

• Partner closely with Digital, Commerce, Brand Partnerships, Product, and International teams (Brazil)
• Collaborate with Brand Partnerships, Sync, and Product teams to unlock additional artist opportunities
• Develop integrated campaigns and content strategies that extend beyond streaming

Requirements

• 8-12+ years of experience in music marketing across artist and/or label environments
• NY-Based or willing to relocate
• Senior leadership experience building and managing teams
• Track record of developing and executing successful marketing strategies
• Experience working cross-functionally at an executive level
• Strong operational and financial acumen
• Experience in fast-moving, high-growth organizations preferred

Salary Hiring Range:

$200,000 - $260,000 + bonus eligibility

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The Common Engineering Components (CEC) team, part of Synopsys Central Engineering, develops and maintains productivity-enhancing platforms, tools, and services enabling Synopsys R&D engineers, Field Application Engineers (FAEs), and customers to efficiently identify, diagnose, and resolve issues in Synopsys' Electronic Design Automation (EDA) tools. Our work is critical to the performance and scalability of EDA solutions used in silicon chip design.

We are looking for a Senior Staff Software Engineer to join our team. As a Senior Staff Software Engineer, you will be responsible for delivering enterprise-scale software solutions to internal and external stakeholders, ensuring reliability and performance at every stage. You will collaborate with multiple global engineering teams to achieve common goals and successful project delivery. You will define technical requirements and drive implementation of next-generation productivity platforms. You will mentor engineers, fostering a culture of technical excellence, collaboration, and innovation within the team.

You will utilize C/C++, Python, Unix/Linux system-level knowledge, and advanced debugging and performance profiling tools to deliver robust, scalable solutions and resolve critical issues efficiently. You will accelerate Synopsys' capability to deliver cutting-edge solutions for customers and partners worldwide. You will enable seamless integration of advanced computing platforms into chip design and verification workflows. You will drive operational efficiency and scalability for mission-critical applications and services. You will influence technology strategy and architecture decisions, shaping the future of Synopsys' product offerings. You will empower engineering teams through mentorship, fostering innovation and technical growth. You will enhance customer satisfaction by delivering reliable, high-performance software solutions tailored to evolving industry needs.

You will have 8–14 years of professional software development experience, ideally in High Performance Computing (HPC) or large-scale systems. You will have strong Unix/Linux systems programming background, including multithreading, synchronization, sockets, and inter-process communication (IPC). You will have proven experience designing and working with distributed systems, including networking, databases, and containerized environments. You will have proficiency in C/C++ and Python, with hands-on experience using debugging and performance profiling tools. You will have excellent written and verbal communication skills, with the ability to explain complex technical concepts to diverse audiences.

You will be an inclusive leader and collaborator, committed to fostering diverse perspectives and teamwork. You will be analytical and detail-oriented, with a passion for solving challenging technical problems. You will be adaptable and proactive, able to thrive in dynamic, rapidly evolving environments. You will be curious and innovative, always seeking new ways to leverage technology for impactful results. You will be a mentor and coach, dedicated to supporting the growth and development of others.

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role:

Anthropic's performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast paced, dynamic environment.

Responsibilities:

• Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
• Become familiar with the team’s technical stack enough to make targeted contributions as an individual contributor
• Manage day-to-day execution of the team's work
• Prioritize the team’s work and manage projects in a highly dynamic, fast paced environment
• Coach and support your reports in understanding, and pursuing, their professional growth
• Maintain a deep understanding of the team's technical work and its implications for AI safety

You may be a good fit if you:

• Have 1+ years of management experience in a technical environment, particularly performance or distributed systems
• Have a background in machine learning, AI, or a similar related technical field
• Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
• Excel at building strong relationships with stakeholders at all levels
• Are a quick learner, capable of understanding and contributing to discussions on complex technical topics
• Have experience managing teams through periods of rapid growth and change
• Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level of abstraction) to be effective

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship:

We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification.

Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

Your safety matters to us.

To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and paid time off, and a comprehensive benefits package.

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As a TPU Kernel Engineer, you'll be responsible for identifying and addressing performance issues across many different ML systems, including research, training, and inference. A significant portion of this work will involve designing and optimising kernels for the TPU. You will also provide feedback to researchers about how model changes impact performance.

You may be a good fit if you:

• Have significant experience optimising ML systems for TPUs, GPUs, or other accelerators
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to learn more about machine learning research
• Care about the societal impacts of your work

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• Designing and implementing kernels for TPUs or other ML accelerators
• Understanding accelerators at a deep level, e.g. a background in computer architecture
• ML framework internals
• Language modeling with transformers

Representative projects:

• Implement low-latency, high-throughput sampling for large language models
• Adapt existing models for low-precision inference
• Build quantitative models of system performance
• Design and implement custom collective communication algorithms
• Debug kernel performance at the assembly level

Logistics

• Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

Guidance on Candidates' AI Usage:

Learn about our policy for using AI in our application process

Apply for this job

• indicates a required field

First Name Last Name Email Country Phone* 244 results found No results found

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

You may be a good fit if you:

• Have significant software engineering experience
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to learn more about machine learning research
• Care about the societal impacts of your work

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• GPUs, Kubernetes, Pytorch, or OS internals
• Language modeling with transformers
• Reinforcement learning
• Large-scale ETL

Representative projects:

• Optimizing the throughput of a new attention mechanism
• Comparing the compute efficiency of two Transformer variants
• Making a Wikipedia dataset in a format models can easily consume
• Scaling a distributed training job to thousands of GPUs
• Writing a design doc for fault tolerance strategies
• Creating an interactive visualization of attention between tokens in a language model

Annual compensation range for this role is listed below.

Annual Salary:

$350,000 - $500,000USD

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in California, USA.

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You want to build the cutting-edge systems that train AI models like Claude. You're excited to work at the frontier of machine learning, implementing and improving advanced techniques to create ever more capable, reliable and steerable AI. As an ML Systems Engineer on our Reinforcement Learning Engineering team, you'll be responsible for the critical algorithms and infrastructure that our researchers depend on to train models. Your work will directly enable breakthroughs in AI capabilities and safety. You'll focus obsessively on improving the performance, robustness, and usability of these systems so our research can progress as quickly as possible. You're energized by the challenge of supporting and empowering our research team in the mission to build beneficial AI systems.

Our finetuning researchers train our production Claude models, and internal research models, using RLHF and other related methods. Your job will be to build, maintain, and improve the algorithms and systems that these researchers use to train models. You’ll be responsible for improving the speed, reliability, and ease-of-use of these systems.

You may be a good fit if you:

• Have 4+ years of software engineering experience
• Like working on systems and tools that make other people more productive
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to learn more about machine learning research
• Care about the societal impacts of your work

Strong candidates may also have experience with:

• High performance, large scale distributed systems
• Large scale LLM training
• Python
• Implementing LLM finetuning algorithms, such as RLHF

Representative projects:

• Profiling our reinforcement learning pipeline to find opportunities for improvement
• Building a system that regularly launches training jobs in a test environment so that we can quickly detect problems in the training pipeline
• Making changes to our finetuning systems so they work on new model architectures
• Building instrumentation to detect and eliminate Python GIL contention in our training code
• Diagnosing why training runs have started slowing down after some number of steps, and fixing it
• Implementing a stable, fast version of a new training algorithm proposed by a researcher

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior

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Running machine learning (ML) algorithms at our scale often requires solving novel systems problems. As a Performance Engineer, you'll be responsible for identifying these problems, and then developing systems that optimize the throughput and robustness of our largest distributed systems. Strong candidates here will have a track record of solving large-scale systems problems and will be excited to grow to become an expert in ML also.

You may be a good fit if you:

• Have significant software engineering or machine learning experience, particularly at supercomputing scale
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to learn more about machine learning research
• Care about the societal impacts of your work

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

Representative projects:

• Implement low-latency high-throughput sampling for large language models
• Implement GPU kernels to adapt our models to low-precision inference
• Write a custom load-balancing algorithm to optimize serving efficiency
• Build quantitative models of system performance
• Design and implement a fault-tolerant distributed system running with a complex network topology
• Debug kernel-level network latency spikes in a containerized environment

Deadline to apply:

None. Applications will be reviewed on a rolling basis.

Logistics

• Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

Guidance on Candidates' AI Usage:

Learn about our policy for using AI in our application process

Apply for this job

• indicates a required field

First Name Last Name Email Country Phone* 244 results found No results found

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Anthropic's performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams, you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast-paced, dynamic environment.

Responsibilities:

• Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
• Become familiar with the team's technical stack enough to make targeted contributions as an individual contributor
• Manage day-to-day execution of the team's work
• Prioritize the team's work and manage projects in a highly dynamic, fast-paced environment
• Coach and support your reports in understanding, and pursuing, their professional growth
• Maintain a deep understanding of the team's technical work and its implications for AI safety

You may be a good fit if you:

• Have 1+ years of management experience in a technical environment, particularly performance or distributed systems
• Have a background in machine learning, AI, or a similar related technical field
• Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
• Excel at building strong relationships with stakeholders at all levels
• Are a quick learner, capable of understanding and contributing to discussions on complex technical topics
• Have experience managing teams through periods of rapid growth and change
• Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you'll need to understand (at a high level of abstraction) to be effective

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

Logistics

• Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic, we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave policies, and a dynamic and inclusive work environment.

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San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $266K – $445K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

OpenAI’s Hardware team designs the custom silicon that powers the world’s most advanced AI systems. From system-level architecture to custom circuit implementations, we partner closely with model and infrastructure teams to deliver performance, power, and efficiency breakthroughs across all layers of the stack.

About the Role

We are seeking a highly skilled Silicon Implementation Engineer with deep expertise in physical design and methodology. This individual contributor role sits within our physical design team and is central to delivering power, performance, and area (PPA) optimized datapath and interconnect solutions for next-generation AI accelerators.

You’ll work closely with RTL designers to define and execute on physical design strategies. You will develop tools, flows and methodologies to increase team productivity. Your work will directly impact silicon’s performance and cost efficiency, as well as the team’s execution velocity and quality.

In this role, you will:

• Develop, build and own tools, flows and methodologies for physical implementation
• Own physical implementation of floorplan blocks from floorplanning to final signoff
• Collaborate with RTL designers to drive optimal block implementation solutions
• Analyze and optimize design for timing, power, and area trade-offs, working in collaboration with EDA vendors and ASIC partners

Qualifications:

• BS w/ 4+ or MS with 2+ years or PhD with 0-1 year(s) of relevant industry experience in physical design and methodology development
• Demonstrated success in taping out complex silicon designs
• Hands-on experience with block physical implementation and PPA convergence
• Strong coding experience with python, bazel, TCL
• Strong experience building physical design tools, flows and methodologies
• Strong understanding of microarchitecture, RTL design, physical design, circuit design, physical verification and timing closure.
• Deep familiarity with industry-standard tools and flows for physical synthesis, PNR, LEC and power estimation

Bonus:

• Experience with AI or HPC-focused chips
• Experience with optimizing PPA for high performance compute cores
• Hands-on experience with top-level design methodologies

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Microsoft AI are looking for a talented Member of Technical Staff, High Performance Computing Engineer at their London office. This role sits at the heart of building and scaling the infrastructure that trains their frontier models and powers the next evolution of their personal AI, Copilot. You'll work directly with researchers and engineers to support their workloads, troubleshoot cluster usage issues, and triage failed or underperforming jobs to resolution.

About the Role

As a Member of Technical Staff, High Performance Computing Engineer, you will design, operate, and maintain large-scale HPC environments, drawing on hands-on engineering experience in production settings. You will own the deployment, configuration, and day-to-day operation of HPC schedulers (e.g., SLURM, Kubernetes), ensuring reliable and efficient job scheduling at scale. You will serve as a technical owner for at least one core HPC domain (GPU compute, high-performance storage, networking, or similar), including ongoing maintenance, performance tuning, and troubleshooting of massive clusters.

Accountabilities

• Design, operate, and maintain large-scale HPC environments, drawing on hands-on engineering experience in production settings.
• Own the deployment, configuration, and day-to-day operation of HPC schedulers (e.g., SLURM, Kubernetes), ensuring reliable and efficient job scheduling at scale.
• Serve as a technical owner for at least one core HPC domain (GPU compute, high-performance storage, networking, or similar), including ongoing maintenance, performance tuning, and troubleshooting of massive clusters.

The Candidate we're looking for

Experience:

• 4+ years technical engineering experience with deploying or operating on-premise or cloud high-performance clusters.
• 4+ years experience working with high-scale training clusters (ex. working with frameworks/tools such as nvidia InfiniBand clusters, SLURM, Kubernetes, Ray, etc.).
• 4+ years experience building scalable services on top of public cloud infrastructure like Azure, AWS, or GCP.

Technical skills:

• Experience with LLM training clusters.
• Experience working with AI platforms, frameworks, and APIs.
• Experience using Machine Learning frameworks, including experience using, deploying, and scaling language learning models, either personally or professionally.

Personal attributes:

• Ability to identify, analyze, and resolve complex technical issues, ensuring optimal performance, scalability, and user experience.
• Dedication to writing clean, maintainable, and well-documented code with a focus on application quality, performance, and security.

Benefits

• Competitive salary and benefits package.
• Opportunity to work with a leading technology company and contribute to HERE's mission.
• Collaborative and dynamic work environment.
• Professional development opportunities.

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Microsoft AI are looking for experienced Member of Technical Staff, High Performance Computing Engineers to help build and scale the infrastructure that trains their frontier models and powers the next evolution of their personal AI, Copilot.

About the Role

This role offers the unique opportunity to work on some of the largest scale supercomputers in the world – a rare chance to operate at such a significant scale. As a Member of Technical Staff, High Performance Computing Engineer, you will design, operate, and maintain large-scale HPC environments, drawing on hands-on engineering experience in production settings. You will own the deployment, configuration, and day-to-day operation of HPC schedulers (e.g., SLURM, Kubernetes), ensuring reliable and efficient job scheduling at scale.

Accountabilities

• Design, operate, and maintain large-scale HPC environments, drawing on hands-on engineering experience in production settings.
• Own the deployment, configuration, and day-to-day operation of HPC schedulers (e.g., SLURM, Kubernetes), ensuring reliable and efficient job scheduling at scale.

The Candidate we're looking for

Experience:

• 4+ years technical engineering experience with deploying or operating on-premise or cloud high-performance clusters.
• 4+ years experience working with high-scale training clusters (ex. working with frameworks/tools such as nvidia InfiniBand clusters, SLURM, Kubernetes, Ray, etc.).
• 4+ years experience building scalable services on top of public cloud infrastructure like Azure, AWS, or GCP.

Technical skills:

• Experience with LLM training clusters.
• Experience working with AI platforms, frameworks, and APIs.
• Experience using Machine Learning frameworks, including experience using, deploying, and scaling language learning models, either personally or professionally.

Personal attributes:

• Ability to identify, analyze, and resolve complex technical issues, ensuring optimal performance, scalability, and user experience.
• Dedication to writing clean, maintainable, and well-documented code with a focus on application quality, performance, and security.

Benefits

• Competitive salary.
• Comprehensive benefits package.
• Opportunities for professional growth and development.

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What you'll do

As a Software Developer, you will be responsible for developing, implementing, and maintaining combustion and reactive-flow models within a finite volume CFD solver environment. You will also enhance numerical algorithms to improve stability, accuracy, and computational performance, including adaptation for parallel and high performance computing environments.

What you need

• PhD in Mechanical Engineering, Chemical Engineering, Physics, Computational Engineering, or a related technical discipline
• Strong theoretical understanding of combustion, fluid mechanics, thermodynamics, and heat transfer
• Experience with finite volume CFD methods and numerical discretization techniques
• Proficiency in C++ or Fortran for scientific or engineering software development; additional experience with Python is advantageous

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