member of technical staff

<div>
 
 
 ABOUT xAI
 
 
 
 
 xAI&rsquo;s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge.
 
 
 Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity.
 
 
 We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company&rsquo;s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important.
 
 
 All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.
 
 
 
 ABOUT THE ROLE:
 
 
 As a Member of Technical Staff, you will build frameworks to improve the reasoning capability, build distributed reinforcement learning systems, techniques for inference time compute (e.g. tree search and planning), and develop environments for agents.
 
 
 You will get exposure and will be expected to solve and take ownership of components across the entire stack.
 
 
 RESPONSIBILITIES:
 
 <ul>
 <li>
 Build robust and scalable distributed RL systems.
 </li>
 <li>
 Optimise frameworks to enable complex inference-time reasoning.
 </li>
 <li>
 Develop environments and harnesses for agents.
 </li>
 </ul>
 
 BASIC QUALIFICATIONS:
 
 <ul>
 <li>
 Experienced with large-scale reinforcement learning systems.
 </li>
 <li>
 Designing and implementing distributed systems.
 </li>
 <li>
 Keeping up with state-of-the-art RL and inference time compute algorithms.
 </li>
 </ul>
 
 COMPENSATION AND BENEFITS:
 
 
 &pound;107,000 - &pound;262,000 GBP
 
 
 Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive healthcare and dental coverage, cash plan, income protection, life insurance, and various other discounts and perks.
 
 
 
 xAI is an equal opportunity employer. For details on data processing, view our&nbsp;
 
 
 Recruitment Privacy Notice.
 
 
</div>

Member of Technical Staff - Reasoning

ellamind

<div>Agents are only as good as the team behind them. We're experienced researchers and engineers building vertical AI agents that run in production inside some of the most demanding environments there are: health insurers, banks, and the public sector, where decisions are audited and mistakes carry real consequences.
We're looking for a strong generalist who's comfortable moving across the stack and isn't fenced into one specialty, the kind of engineer who can follow a problem from the frontend down to the infrastructure and into the AI layer. Agents are a big part of how you cover that ground. The twist that makes this role unusual: you use agents to improve agents. You'll wield agentic coding tools to build, evaluate, and harden the production AI agents we ship to customers, and feed what you learn straight back into making the next ones better. You go wherever the hard problem is, and you understand what's happening underneath, in the systems you build and in the models and agents themselves.<h1 class="jobSectionHeader"> 
What you'll do</h1><ul><li>
Use agents to improve agents. Wield agentic coding tools (Claude, Codex, ...) to build, evaluate, and harden the production agents we ship, then fold what you learn back into faster, better tooling and stronger agents for the next use case. The better you get at directing agents, the better the agents you ship.</li><li>
Work across the stack. Frontend, backend, infrastructure, data, and the AI layer. You go where the problem is instead of waiting for it to land in your lane.</li><li>
Build and ship production AI agents. Take agents from prototype to production inside regulated environments: orchestration, tool use, messy real-world inputs, and the reliability and auditability real operations demand.</li><li>
Own things end-to-end. From a vague problem to a deployed, reliable system: design it, build it, deploy it, and keep it running.</li><li>
Go deep when it counts. Understand the systems beneath the surface, distributed systems behavior, infra, and how LLMs and agents actually work, so you can debug what others can't and make good calls under uncertainty.</li><li>
Stay ahead. The tools and models change every few weeks. You test new releases early and translate what works into how you and the team build.</li></ul><h1 class="jobSectionHeader">
What we're looking for</h1>
Must-haves<ul><li>
Generalist range: you're excellent in at least one area and genuinely comfortable working outside it. You don't need to be an expert in everything; you need to be the kind of person who picks up an unfamiliar part of the stack and gets productive fast, with agents helping you go further.</li><li>
Fluency with coding agents as your default way of working. You can point to specific workflows, failure modes, and things you've actually built or shipped with agents, not just tried.</li><li>
A real mental model of how LLMs and agents work: why they fail, how to evaluate them, and how to make non-deterministic systems dependable.</li><li>
Strong engineering judgment: you read unfamiliar code critically, catch when an agent has gone off track, and know what good architecture looks like.</li><li>
Enthusiasm about AI and its applications. In software development and beyond.</li><li>
On-site collaboration 3 days/week in Berlin or Bremen. Travel to our Bremen HQ during onboarding.</li><li>
Fluency in English (at least B2).</li><li>
Valid EU work authorization.</li></ul>
Nice-to-haves<ul><li>
Depth in one area that complements the breadth (e.g. distributed systems, infra/DevOps, full-stack, or applied AI/LLMs).</li><li>
Experience building agent systems: orchestration, tool use, evaluation, or agent frameworks.</li><li>
Experience taking AI from prototype to production, not just demos.</li><li>
Experience in regulated industries (insurance, banking, public sector) or other compliance-heavy domains.</li><li>
German language skills.</li><li>
Open-source contributions or public writing on agents, applied AI, or agentic workflows.</li></ul>
What matters most
We prioritize demonstrated excellence in your projects and career. If you&rsquo;re motivated to build and optimize AI solutions, we want to hear from you, even if you don&rsquo;t meet every single criterion.<h1 class="jobSectionHeader">
Why us?</h1><ul><li>
Shape the future of AI development: You'll have real influence over our products and technical direction, helping decide how AI agents get built, evaluated, and deployed in the environments where it's hardest to get right.</li><li>
Always at the frontier: You'll work with the newest models and techniques the moment they land, on the problems that make agents actually function in production: orchestrating multi-step workflows, integrating and switching across LLMs, building robust evaluation and guardrails, handling messy real-world inputs (PDFs, scans, voice), and engineering for auditability and reliability under regulatory constraints. Modern, well-architected systems, no legacy baggage holding you back.</li><li>
Career-defining opportunity: AI agents are about to reshape how entire regulated industries operate, and getting them out of the demo and into real operations is the hardest, most valuable problem in the field right now. Almost no one has done it inside environments like health insurers, banks, and public institutions. You'll be one of the people who builds them first, and walk away with expertise and a track record that very few engineers in the world can claim.</li><li>
Ownership and impact: Get full end-to-end ownership of the agents and systems you build, direct collaboration with AI researchers and engineers, and immediate feedback on how your work helps customers ship reliable AI. Your engineering decisions directly shape agents that make real, audited decisions in production.</li><li>
Competitive package with upside: In addition to a competitive salary, we offer a VSOP (Virtual Stock Option Program) to give you a stake in the company&rsquo;s success as we grow.</li><li>
Best-in-class development experience: Generous, no-friction access to all the AI tools and platforms that make your day-to-day faster, so you spend your time on hard problems, not on overhead.</li><li>
Work environment: Our Bremen office features stunning waterfront views, complimentary beverages, smoothies, and a boat. We also have an office in Berlin, giving you flexibility across both locations.</li><li>
Grow with transformative technology: Build deep expertise in AI agents, evaluation and infrastructure alongside our expanding team, mastering the technologies that are reshaping entire industries.</li></ul><h1 class="jobSectionHeader">
About ellamind</h1>
We build the tools enterprises need to trust, deploy, and scale AI agents. elluminate evaluates LLMs and agents with evidence instead of guesswork; ellarun deploys them securely in hours, not months; and the ellaverse provides realistic, domain-specific, rigorously validated environments to put agents through their paces before they ever reach a customer. We like owning problems end-to-end, shipping pragmatically, and giving back to the open-source community. We're cash-flow positive, with offices in Bremen (HQ) and Berlin.
Compensation Range: &euro;80K - &euro;125K</div>

Member of Technical Staff - Agent Engineer

<div>
 Agents are only as good as the team behind them. We're experienced researchers and engineers building vertical AI agents that run in production inside some of the most demanding environments there are: health insurers, banks, and the public sector, where decisions are audited and mistakes carry real consequences.
 
 
 We're looking for a strong generalist who's comfortable moving across the stack and isn't fenced into one specialty, the kind of engineer who can follow a problem from the frontend down to the infrastructure and into the AI layer. Agents are a big part of how you cover that ground. The twist that makes this role unusual: you use agents to improve agents. You'll wield agentic coding tools to build, evaluate, and harden the production AI agents we ship to customers, and feed what you learn straight back into making the next ones better. You go wherever the hard problem is, and you understand what's happening underneath, in the systems you build and in the models and agents themselves.
 
 
 
 
 What you'll do
 
 
 
 
 <ul>
 <li>
 Use agents to improve agents. Wield agentic coding tools (Claude, Codex, ...) to build, evaluate, and harden the production agents we ship, then fold what you learn back into faster, better tooling and stronger agents for the next use case. The better you get at directing agents, the better the agents you ship.
 </li>
 <li>
 Work across the stack. Frontend, backend, infrastructure, data, and the AI layer. You go where the problem is instead of waiting for it to land in your lane.
 </li>
 <li>
 Build and ship production AI agents. Take agents from prototype to production inside regulated environments: orchestration, tool use, messy real-world inputs, and the reliability and auditability real operations demand.
 </li>
 <li>
 Own things end-to-end. From a vague problem to a deployed, reliable system: design it, build it, deploy it, and keep it running.
 </li>
 <li>
 Go deep when it counts. Understand the systems beneath the surface, distributed systems behavior, infra, and how LLMs and agents actually work, so you can debug what others can't and make good calls under uncertainty.
 </li>
 <li>
 Stay ahead. The tools and models change every few weeks. You test new releases early and translate what works into how you and the team build.
 
 
 </li>
 </ul>
 
 
 What we're looking for
 
 
 
 
 
 Must-haves
 
 
 
 <ul>
 <li>
 Generalist range: you're excellent in at least one area and genuinely comfortable working outside it. You don't need to be an expert in everything; you need to be the kind of person who picks up an unfamiliar part of the stack and gets productive fast, with agents helping you go further.
 </li>
 <li>
 Fluency with coding agents as your default way of working. You can point to specific workflows, failure modes, and things you've actually built or shipped with agents, not just tried.
 </li>
 <li>
 A real mental model of how LLMs and agents work: why they fail, how to evaluate them, and how to make non-deterministic systems dependable.
 </li>
 <li>
 Strong engineering judgment: you read unfamiliar code critically, catch when an agent has gone off track, and know what good architecture looks like.
 </li>
 <li>
 Enthusiasm about AI and its applications. In software development and beyond.
 </li>
 <li>
 On-site collaboration &ge;3 days/week in Berlin or Bremen. Travel to our Bremen HQ during onboarding.
 </li>
 <li>
 Fluency in English (at least B2).
 </li>
 <li>
 Valid EU work authorization.
 
 
 </li>
 </ul>
 
 Nice-to-haves
 
 
 
 <ul>
 <li>
 Depth in one area that complements the breadth (e.g. distributed systems, infra/DevOps, full-stack, or applied AI/LLMs).
 </li>
 <li>
 Experience building agent systems: orchestration, tool use, evaluation, or agent frameworks.
 </li>
 <li>
 Experience taking AI from prototype to production, not just demos.
 </li>
 <li>
 Experience in regulated industries (insurance, banking, public sector) or other compliance-heavy domains.
 </li>
 <li>
 German language skills.
 </li>
 <li>
 Open-source contributions or public writing on agents, applied AI, or agentic workflows.
 
 
 </li>
 </ul>
 
 What Matters Most
 
 
 
 We prioritize
 
 demonstrated excellence in your projects and career
 
 . If you&rsquo;re motivated to build and optimize AI solutions, we want to hear from you, even if you don&rsquo;t meet every single criterion.
 
 
 
 
 Why us?
 
 
 
 
 <ul>
 <li>
 Shape the future of AI development: You'll have real influence over our products and technical direction, helping decide how AI agents get built, evaluated, and deployed in the environments where it's hardest to get right.
 </li>
 <li>
 Always at the frontier: You'll work with the newest models and techniques the moment they land, on the problems that make agents actually function in production: orchestrating multi-step workflows, integrating and switching across LLMs, building robust evaluation and guardrails, handling messy real-world inputs (PDFs, scans, voice), and engineering for auditability and reliability under regulatory constraints. Modern, well-architected systems, no legacy baggage holding you back.
 </li>
 <li>
 Career-defining opportunity: AI agents are about to reshape how entire regulated industries operate, and getting them out of the demo and into real operations is the hardest, most valuable problem in the field right now. Almost no one has done it inside environments like health insurers, banks, and public institutions. You'll be one of the people who builds them first, and walk away with expertise and a track record that very few engineers in the world can claim.
 </li>
 <li>
 Ownership and impact: Get full end-to-end ownership of the agents and systems you build, direct collaboration with AI researchers and engineers, and immediate feedback on how your work helps customers ship reliable AI. Your engineering decisions directly shape agents that make real, audited decisions in production.
 </li>
 <li>
 Competitive package with upside: In addition to a competitive salary, we offer a VSOP (Virtual Stock Option Program) to give you a stake in the company&rsquo;s success as we grow.
 </li>
 <li>
 Best-in-class development experience: Generous, no-friction access to all the AI tools and platforms that make your day-to-day faster, so you spend your time on hard problems, not on overhead.
 </li>
 <li>
 Work environment: Our Bremen office features stunning waterfront views, complimentary beverages, smoothies, and a boat. We also have an office in Berlin, giving you flexibility across both locations.
 </li>
 <li>
 Grow with transformative technology: Build deep expertise in AI agents, evaluation and infrastructure alongside our expanding team, mastering the technologies that are reshaping entire industries.
 
 
 </li>
 </ul>
 
 About Ellamind
 
 
 
 We build the tools enterprises need to trust, deploy, and scale AI agents. elluminate evaluates LLMs and agents with evidence instead of guesswork; ellarun deploys them securely in hours, not months; and the ellaverse provides realistic, domain-specific, rigorously validated environments to put agents through their paces before they ever reach a customer. We like owning problems end-to-end, shipping pragmatically, and giving back to the open-source community. We're cash-flow positive, with offices in Bremen (HQ) and Berlin.
 
 
 Compensation Range: &euro;80K - &euro;125K
 
 
</div>

GlobalFoundries

<div>About GlobalFoundries:
 
GlobalFoundries is a leading full-service semiconductor foundry providing a unique combination of design, development, and fabrication services to some of the world&rsquo;s most inspired technology companies. With a global manufacturing footprint spanning three continents, GlobalFoundries makes possible the technologies and systems that transform industries and give customers the power to shape their markets. For more information, visit www.gf.com.
Summary of Role:
Fab 9 is seeking a Pump, Chiller and Scrubber MTS Equipment Engineer. The individual selected for this position will be part of the Manufacturing Engineering organization with responsibilities focused on the performance of vacuum pumps, chillers and various abatement systems used in Fab 9. Responsibilities will include activities associated with cost of ownership, tool performance, and strategic planning. Cross functional activities will include partnering with equipment engineers, facilities, environmental, quality, logistics, global supply management and contract repair personnel.
Essential Responsibilities:
<ul><li>Deliver uniform solutions to improve cost of ownership of Fab9 pumps, chillers, and scrubbers.</li>
<li>Improve preventative + corrective maintenance procedures &amp; root cause understanding to improve uptime performance and equipment stability</li>
<li>Launch and drive new programs that track pump fail modes across the factory and drive chronic fail improvement.</li>
<li>Drive Strategic Planning / Capex to enable investments that achieve longer lifetimes, commonality, and address obsolescence.</li>
<li>Contribute to ONEGF benchmarking to share and learn best practices with other PCS teams.</li>
<li>Leverage on-site MES and ERC repair where applicable</li>
<li>Partner with inventory planning team to ensure cost avoidance of new buys with properly planned rework loops</li>
<li>Improve Supplier Quality by defining incoming quality requirements to improve first time right, improve warranty claim recovery rate, and reduce DOA rate.</li>
<li>Own Pump and Chiller Service contracts in Fab 9, defining key metrics to measure service contract performance.</li>
<li>Lead onsite PCS team: Interlocking with team, Prioritizing tool downs, expanding scope of the team, and improving the work.</li>
<li>Must be mechanically inclined and able to lead hands on, tactical troubleshooting efforts to resolve long term performance issues; must be able to deconstruct and understand complex systems</li>
</ul>Other Responsibilities
<ul><li>Perform all activities in a safe and responsible manner and support all Environmental, Health, Safety &amp; Security requirements, and programs</li>
<li>Other duties as assigned by manager / supervisor</li> 
</ul> 
Required Qualifications:
<ul><li>Education - Bachelor&rsquo;s degree in Mechanical Engineering, Electrical Engineering, Materials Science, Solid State Physics or other relevant discipline + 6-7 years of experience or MS + 5-6 years relevant experience or PhD + 3-4 years' relevant experience</li>
<li>Experience - minimum 6-7 years technical equipment experience working on 200mm/300mm semiconductor platforms</li>
<li>Understanding and knowledge of Statistical Process Control (SPC) and Design of Experiments (DOE).</li>
<li>Ability to work effectively and efficiently with diverse teams, customers, internal and external partners.</li>
<li>Language Fluency - English (both Written &amp; Verbal)</li>
<li>Minimum of 10% travel may be required.</li>
</ul>Preferred Qualifications
 
N/A 
 
 
Expected Salary Range
$98,000.00 - $176,000.00
The exact Salary will be determined based on qualifications, experience and location.
<div>If you need a reasonable accommodation for any part of the employment process, please contact us by email at usaccommodations@gf.com and let us know the nature of your request and your contact information. Requests for accommodation will be considered on a case-by-case basis. Please note that only inquiries concerning a request for reasonable accommodation will be responded to from this email address. 
</div><div>An offer with GlobalFoundries is conditioned upon the successful completion of pre-employment conditions, as applicable, and subject to applicable laws and regulations. 
</div><div>GlobalFoundries is fully committed to equal opportunity in the workplace and believes that cultural diversity within the company enhances its business potential. GlobalFoundries goal of excellence in business necessitates the attraction and retention of highly qualified people. Artificial barriers and stereotypic biases detract from this objective and may be illegally discriminatory. 
</div><div>All policies and processes which pertain to employees including recruitment, selection, training, utilization, promotion, compensation, benefits, extracurricular programs, and termination are created and implemented without regard to age, ethnicity, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, sexual orientation, gender identity or expression, veteran status, or any other characteristic or category specified by local, state or federal law</div></div>

Member of Technical Staff - Equipment Engineering

Cohere

<div>
 
 Who are we?
 
 
 
 Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.
 
 
 We&rsquo;re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.
 
 
 We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.
 
 
 We are a global technology company co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Join us!
 
 
 
 Why this role?
 
 
 
 As a Member of Technical Staff on our Applied ML team, you will work directly with customers to quickly understand their greatest problems and design and implement solutions using Large Language Models.
 
 
 You&rsquo;ll apply your problem-solving ability, creativity, and technical skills to close the last-mile gap in Enterprise AI adoption. You&rsquo;ll be able to deliver products like early startup CTOs/CEOs do and disrupt some of the most important industries and institutions globally!
 
 
 
 As a Senior Member Of Technical Staff, You Will
 
 
 
 <ul>
 <li>
 Plan and execute large-group projects that carry through from ideation to production.Bring cross-functional alignment across engineering, product and other disciplines.
 </li>
 <li>
 Mentor a distributed team of engineers in subject matter expertise. Identify opportunities and gaps in existing models and strategize what to work on.
 </li>
 <li>
 Work closely with product teams to develop solutions.
 </li>
 <li>
 Engage in collaborations with our partner organizations.
 </li>
 <li>
 Assist our legal teams with preparation of patents on developed IP.
 </li>
 <li>
 Join us at a pivotal moment, shape what we build and wear multiple hats!
 
 
 </li>
 </ul>
 
 You May Be a Good Fit If You Have
 
 
 
 <ul>
 <li>
 Prior experience in leading ML teams in applied research and production.
 </li>
 <li>
 Prior experience in setting as well as executing technical direction to build new or to refine existing products.
 </li>
 <li>
 Prior experience in working cross-discipline in matrixed organizations.
 </li>
 <li>
 Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR.
 </li>
 <li>
 Experience using large-scale distributed training and inference.
 </li>
 <li>
 Strong mentorship, communication, and problem-solving skills.
 </li>
 <li>
 A demonstrated passion for applied ML models and products.
 </li>
 <li>
 Working proficiency in Arabic.
 </li>
 <li>
 Bonus: experience working for B2B companies in the ML space.
 </li>
 <li>
 This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We have a wide variety of backgrounds at Cohere.
 
 
 </li>
 </ul>
 
 How And Where We Work
 
 
 
 <ul>
 <li>
 Cohere is remote-friendly. We have offices in Toronto, San Francisco, New York City, London, Paris, Montreal, and more coming soon.
 </li>
 <li>
 For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
 </li>
 <li>
 For those not near an office: a co-working benefit so you can work alongside others in your city.
 
 
 </li>
 </ul>
 If any of the above doesn&rsquo;t line up exactly with your experience, we still encourage you to apply.
 
 
 We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.
 
 
 We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.
</div>

Senior Member of Technical Staff, MLE (Middle East)

<div>
 
 Who are we?
 
 
 
 Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.
 
 
 We&rsquo;re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.
 
 
 We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.
 
 
 We are a global technology company co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Join us!
 
 
 
 Why this role?
 
 
 
 As a Member of Technical Staff on our Applied ML team, you will work directly with customers to quickly understand their greatest problems and design and implement solutions using Large Language Models.
 
 
 You&rsquo;ll apply your problem-solving ability, creativity, and technical skills to close the last-mile gap in Enterprise AI adoption. You&rsquo;ll be able to deliver products like early startup CTOs/CEOs do and disrupt some of the most important industries and institutions globally!
 
 
 
 As a Senior Member Of Technical Staff, You Will
 
 
 
 <ul>
 <li>
 Plan and execute large-group projects that carry through from ideation to production.Bring cross-functional alignment across engineering, product and other disciplines.
 </li>
 <li>
 Mentor a distributed team of engineers in subject matter expertise. Identify opportunities and gaps in existing models and strategize what to work on.
 </li>
 <li>
 Work closely with product teams to develop solutions.
 </li>
 <li>
 Engage in collaborations with our partner organizations.
 </li>
 <li>
 Assist our legal teams with preparation of patents on developed IP.
 </li>
 <li>
 Join us at a pivotal moment, shape what we build and wear multiple hats!
 
 
 </li>
 </ul>
 
 You May Be a Good Fit If You Have
 
 
 
 <ul>
 <li>
 Prior experience in leading ML teams in applied research and production.
 </li>
 <li>
 Prior experience in setting as well as executing technical direction to build new or to refine existing products.
 </li>
 <li>
 Prior experience in working cross-discipline in matrixed organizations.
 </li>
 <li>
 Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR.
 </li>
 <li>
 Experience using large-scale distributed training and inference.
 </li>
 <li>
 Strong mentorship, communication, and problem-solving skills.
 </li>
 <li>
 A demonstrated passion for applied ML models and products.
 </li>
 <li>
 Working proficiency in Arabic.
 </li>
 <li>
 Bonus: experience working for B2B companies in the ML space.
 </li>
 <li>
 This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We have a wide variety of backgrounds at Cohere.
 
 
 </li>
 </ul>
 
 Full-Time Employees At Cohere Enjoy These Perks
 
 
 
 <ul>
 <li>
 A weekly lunch stipend of $75/&pound;75 or equivalent in your local currency for lunch.
 </li>
 <li>
 Full health and dental benefits, including a separate budget for mental health.
 </li>
 <li>
 RRSP matching, 401K, Pension Scheme.
 </li>
 <li>
 100% Parental Leave top-up for up to 6 months, for either parent.
 </li>
 <li>
 Annual enrichment benefits:
 
 
 </li>
 </ul>
 Arts &amp; culture, fitness/wellness, quality time, and a workspace improvement credit.
 
 
 Education &amp; learning stipend for conferences, courses, and coaching.
 
 
 <ul>
 <li>
 6 weeks of paid vacation (30 working days!)
 </li>
 <li>
 Budget for traveling to other offices if you are remote, plus an annual company offsite.
 
 
 </li>
 </ul>
 
 How And Where We Work
 
 
 
 <ul>
 <li>
 Cohere is remote-friendly. We have offices in Toronto, San Francisco, New York City, London, Paris, Montreal, and more coming soon.
 </li>
 <li>
 For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
 </li>
 <li>
 For those not near an office: a co-working benefit so you can work alongside others in your city.
 </li>
 <li>
 Everyone receives a $500 home office stipend to set up your workspace properly.
 
 
 </li>
 </ul>
 If any of the above doesn&rsquo;t line up exactly with your experience, we still encourage you to apply.
 
 
 We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.
 
 
 We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.
</div>

Reflection

<div>
 
 Our Mission
 
 
 
 Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI. Our mission: make intelligence open and accessible to all.
 
 
 
 The Roles Mission
 
 
 
 Bridge the gap between research and production by turning cutting-edge algorithms into scalable training systems. You will design and optimize the core infrastructure behind frontier AI models &mdash; from reinforcement learning training loops and distributed GPU training to massive-scale data pipelines.
 
 
 Our systems train models across thousands of GPUs and process petabyte-scale datasets. We care deeply about numerical stability, throughput, and reproducibility.
 
 
 
 What This Team Does
 
 
 
 This team owns and evolves the core infrastructure behind our training systems.
 
 
 
 We Focus On
 
 
 
 <ul>
 <li>
 Reinforcement learning training infrastructure
 </li>
 <li>
 Distributed training and inference systems
 </li>
 <li>
 Experiment infrastructure and reproducibility
 </li>
 <li>
 Large-scale data pipelines
 
 
 </li>
 </ul>
 The goal is to build the engineering foundation that allows researchers to iterate quickly while training models at massive scale.
 
 
 
 About The Role
 
 
 
 You will architect and optimize the core training infrastructure that powers our models. This includes RL training loops, distributed GPU systems, and large-scale data pipelines.
 
 
 You will work closely with researchers to transform new ideas into reliable, scalable training systems.
 
 
 
 Responsibilities Include
 
 
 
 <ul>
 <li>
 Designing and optimizing large-scale training loops and data pipelines.
 </li>
 <li>
 Implementing state-of-the-art techniques and ensuring they are numerically stable and computationally efficient.
 </li>
 <li>
 Building internal tooling for launching, monitoring, and reproducing complex experiments.
 </li>
 <li>
 Diagnosing deep bottlenecks across the training stack (GPU memory issues, communication overhead, dataloader stalls).
 </li>
 <li>
 Translating research prototypes into reusable, production-grade infrastructure.
 
 
 </li>
 </ul>
 
 What You'll Work With
 
 
 
 
 Distributed Training
 
 
 
 <ul>
 <li>
 GPU parallelism (data, tensor, pipeline, expert)
 </li>
 <li>
 Large-scale distributed training infrastructure
 </li>
 <li>
 Communication optimization (NCCL, RDMA, GPU interconnects)
 </li>
 <li>
 FSDP / ZeRO and model sharding
 
 
 </li>
 </ul>
 Orchestration &amp; Runtime Systems
 
 
 <ul>
 <li>
 Ray, Kubernetes, Slurm
 </li>
 <li>
 Distributed runtimes and async systems
 </li>
 <li>
 Containerization and sandboxing
 
 
 </li>
 </ul>
 Frameworks
 
 
 <ul>
 <li>
 PyTorch
 </li>
 <li>
 JAX
 </li>
 <li>
 Megatron-style training stacks
 </li>
 <li>
 Triton / custom kernels
 
 
 </li>
 </ul>
 Data Infrastructure
 
 
 <ul>
 <li>
 Large-scale dataset curation pipelines
 </li>
 <li>
 Deduplication and filtering systems
 </li>
 <li>
 Tokenization and preprocessing
 </li>
 <li>
 Distributed data processing frameworks
 
 
 </li>
 </ul>
 
 About You
 
 
 
 <ul>
 <li>
 You are a strong software engineer who speaks the language of machine learning.
 </li>
 <li>
 You may not have a PhD, but you know how to implement a research paper.
 </li>
 <li>
 You have deep experience in at least one of the following: Distributed Training &amp; Inference or Data Infrastructure
 </li>
 <li>
 You enjoy working at the boundary between:
 </li>
 <ul>
 <li>
 Machine learning algorithms
 </li>
 <li>
 Distributed systems
 </li>
 <li>
 High-performance computing
 </li>
 </ul>
 <li>
 You care deeply about performance, numerical stability, and reproducibility.
 </li>
 <li>
 You thrive in high-agency environments and enjoy solving hard technical problems.
 
 </li>
 </ul>
 
 What We Offer
 
 
 
 We believe that to make intelligence open and accessible to all, you need to start at the foundation. Joining Reflection means building from the ground up as part of a talent-dense team. You will help define our future as a company, and help define the future of open foundational models.
 
 
 We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.
 
 
 <ul>
 <li>
 Top-tier compensation: Salary and equity structured to recognize and retain our talent globally.
 </li>
 <li>
 Stock options: Everyone who joins and contributes to Reflection's success gets to share in the upside through stock options.
 </li>
 <li>
 Health &amp; wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance.
 </li>
 <li>
 Meals: Lunch and dinner are provided in the office daily.
 </li>
 <li>
 Life &amp; family: 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys.
 </li>
 <li>
 Vacation days: Unlimited paid time off in the U.S. and 30 days in the U.K.
 </li>
 <li>
 Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable.
 </li>
 <li>
 Team building: We have regular off-sites, happy hours, and team celebrations.
 
 
 </li>
 </ul>
</div>

Member of Technical Staff - Research Software Engineer

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Member of Technical Staff - Research Software Engineer