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CuspAI

<div>
 
 About CuspAI
 
 
 
 CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering.
 
 
 We are working on some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the start of what our 'search engine' for next-generation materials will unlock.
 
 
 We invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration. This work matters. Your work matters.
 
 
 
 We&rsquo;re on the cusp of the on-demand materials era. Join us.
 
 
 
 
 The Role
 
 
 
 Due to rapid growth in our core AI capabilities, we are seeking an experienced Applied AI/ML Engineer (Agents) to design and build the intelligent agents that power our autonomous materials discovery engine.
 
 
 
 Your Impact
 
 
 
 You will be instrumental in developing the "artificial brain" of our agentic materials discovery engine. This is responsible for
 
 orchestrating complex, closed-loop scientific workflows, autonomously making decisions, running simulations
 
 ,
 
 and driving experimental campaigns
 
 to find breakthrough materials faster than ever before.
 
 
 Your work will directly accelerate CuspAI&rsquo;s path to finding solutions for global sustainability challenges.
 
 
 
 What You Will Do
 
 
 
 
 Agentic systems
 
 
 
 <ul>
 <li>
 Design the agentic framework that powers our platform to discover new materials. This includes spanning dynamic, multi-stage simulation workflows from literature-grounded hypothesis generation through to computational and experimental validation
 </li>
 <li>
 Build the integration that connects agents to ML models, simulation engines, databases, and heterogeneous compute backends
 </li>
 <li>
 Design pipelines that let agents autonomously plan, schedule, execute, and interpret computational tasks at scale and over long periods of time
 </li>
 <li>
 Use expert annotations from the Chemistry team to drive targeted improvements in agent planning, retrieval, and decision-making
 </li>
 <li>
 Create evaluations to measure the effectiveness of agents
 
 
 </li>
 </ul>
 
 Experimental design
 
 
 
 <ul>
 <li>
 Build agents that perform experimental design &mdash; applying Bayesian optimization, active learning, or related sequential decision-making methods to decide what to compute or measure next, and to balance exploration and exploitation across long-running discovery campaigns
 </li>
 <li>
 Help close the loop between simulation and physical experiments so that outcomes become durable knowledge &mdash; feeding back into what agents know and how their models reason &mdash; compounding across campaigns.
 </li>
 <li>
 Develop strategies for multi-fidelity and multi-objective decision-making, where agents must trade off cost, time, and uncertainty across simulations and physical experiments
 
 
 </li>
 </ul>
 
 Interdisciplinary Collaboration
 
 
 
 <ul>
 <li>
 Work closely with Chemists, Materials Scientists, and the rest of the Agent team to co-develop our core orchestration intelligence
 </li>
 <li>
 Work on customer projects and implement the direct needs required for these projects
 
 
 </li>
 </ul>
 
 Must Have Skills and Qualifications:
 
 
 
 <ul>
 <li>
 You are someone who gets excited about the opportunity to enable scientists to work on world changing challenges in this domain, with a personal interest in the potential applications of the technology that CuspAI is building.
 </li>
 <li>
 Proficiency in the modern ML ecosystem such as PyTorch or JAX, with experience taking ML-driven systems from prototype to production
 </li>
 <li>
 Strong software engineering skills (building systems at scale in a production environment): testing, modular design, CI/CD, and scalable ML operations in production environments
 </li>
 <li>
 If you have a PhD or Masters degree and 4-5 yrs industry experience this would be ideal, but we will also consider you if you have a PhD and slightly less experience in industry
 </li>
 <li>
 You have a proactive builder mentality with a bias toward shipping and iteration
 </li>
 <li>
 Willingness to learn about materials science, and in particular experimental chemistry - to learn the vocabulary of the discipline to meaningfully interact with other stakeholders
 </li>
 <li>
 Experienced in LLM-assisted programming, knowing its strengths and weaknesses thoroughly.
 
 
 </li>
 </ul>
 
 Bonus Points (But Not Critical):
 
 
 
 <ul>
 <li>
 Experience applying ML models specifically for materials science, chemistry, or drug discovery applications
 </li>
 <li>
 Experience with agentic frameworks and building LLM-powered applications
 </li>
 <li>
 Experience with sequential decision-making methods &mdash; Bayesian optimization, active learning, bandits, or reinforcement learning &mdash; applied to real-world systems
 </li>
 <li>
 Advanced agentic-reasoning techniques: planning models, self-improving systems, multi-tool agents, or RLHF/RLAIF workflows
 
 
 </li>
 </ul>
 
 Additional Considerations
 
 
 
 This role could be based in our
 
 Cambridge, London, Amsterdam or Berlin offices
 
 , with the expectation of being
 
 in the office three days per week
 
 . Additionally, there may be regular travel required to our other offices for collaboration and project oversight.
 
 
 Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world.
 
 
 
 What we offer
 
 
 
 <ul>
 <li>
 A competitive salary: We value and reward impact and growth
 </li>
 <li>
 Equity in CuspAI: You have a stake in the success of the company
 </li>
 <li>
 Time off to stay fresh: 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays
 </li>
 <li>
 &lsquo;Gold Standard&rsquo; parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay - we look after you and your family while we work on the most important materials discovery problems together
 </li>
 <li>
 Professional development budget: We invest in your career development so you can stay up to date with the latest industry knowledge or add to your skills to increase impact and growth
 </li>
 <li>
 Solve meaningful problems: See how your work has a direct impact on advancing materials science and solving sustainability and climate-related problems through the creation and application of bleeding-edge SOTA technology and revolutionary techniques
 </li>
 <li>
 True interdisciplinary teamwork: Be part of a deeply collaborative environment bridging AI research, computational chemistry, and experimental science - work with world-class researchers and engineers who enjoy sharing knowledge and supporting each other
 
 
 </li>
 </ul>
 
 Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world.
 
 
 
 
 CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace
 
 . We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law.
 
 
 
 We actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team.
 
 
 
 
 Please let us know If you require any specific adjustments during or after the interview process. We will do everything we can within reason to accommodate.
 
 
 
</div>

Applied AI/ML Engineer (Agents/RL)

CommonAI CIC

<div>
 CommonAI CIC is a non-profit membership organisation, founded on a belief in collaborative engineering for the safe and responsible development of foundational AI technologies. A place where AI startups, enterprises large and small, public sector bodies and academia can share resources and knowledge, to codevelop and grow businesses, fast.
 
 
 We are led by experienced founders, investors and engineers who believe that collaborative engineering drives faster AI innovation and are backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems.
 
 
 
 The Opportunity
 
 
 
 We're seeking a highly skilled foundation model engineer who has experience of building, training, evaluating, and deploying LLMs or multimodal models end-to-end.
 
 
 We are currently building an AI lab with multiple GPU clusters for testing new hardware and software technologies to accelerate machine learning and inference. This exciting role will primarily focus on model development, data pipelines and system performance. You'll work across the full AI lifecycle, from experimentation to scalable deployment, with a strong emphasis on technical depth and rigour.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Design and implement end-to-end LLM training pipelines
 </li>
 <li>
 Source and, where appropriate, preprocess datasets for training and evaluation
 </li>
 <li>
 Fine-tune and optimise open weight models (LLMs, vision, or traditional ML)
 </li>
 <li>
 Build evaluation frameworks and define performance metrics
 </li>
 <li>
 Develop and maintain data pipelines and training workflows
 </li>
 <li>
 Analyse training pipelines and optimise them for latency, cost, and scalability
 </li>
 <li>
 Implement monitoring, logging, and feedback loops for continuous improvement
 </li>
 <li>
 Experiment with modern AI tooling and services to investigate how they can be leveraged
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Proven experience training and fine-tuning LLMs or multimodal models (not just using APIs)
 </li>
 <li>
 Solid understanding of:
 </li>
 <li>
 Model evaluation and validation
 </li>
 <li>
 Overfitting, bias/variance tradeoffs
 </li>
 <li>
 Data quality and feature engineering
 </li>
 <li>
 Proficiency in Python and ML frameworks (e.g. PyTorch, TensorFlow)
 </li>
 <li>
 Experience building and maintaining ML pipelines in production
 </li>
 <li>
 Familiarity with GPU usage and optimisation
 </li>
 <li>
 Ability to debug and improve model performance systematically
 
 
 </li>
 </ul>
 We also value:
 
 
 <ul>
 <li>
 Knowledge of distributed training or large-scale data processing
 </li>
 <li>
 Experience with MLOps tools (CI/CD for ML, experiment tracking, model versioning)
 </li>
 <li>
 Background in applied research or publishing
 </li>
 <li>
 Familiarity with retrieval systems, embeddings, or ranking models
 
 
 </li>
 </ul>
 Ideally you will have a maths or computer science research background with a focus on developing new algorithms or techniques for training and deploying AI models.
 
 
 You may also have been working in industry in a large organisation or start-up with an emphasis on developing and deploying cutting edge machine learning.
 
 
 When applying, please include:
 
 
 <ul>
 <li>
 Links to relevant projects, papers, or GitHub repositories
 </li>
 <li>
 A brief description of a model/system you trained and deployed end-to-end
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 A collaborative and supportive work environment
 </li>
 <li>
 The opportunity to have a high impact in a growing organisation
 </li>
 <li>
 Competitive salary package and pension
 </li>
 <li>
 Professional development opportunities
 </li>
 <li>
 Networking opportunities with influential people from across the tech sector and academia
 </li>
 <li>
 A vibrant office environment located a few minutes' walk away from Cambridge train station
 
 
 </li>
 </ul>
 
 CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace.
 
</div>

Foundation Model Engineer

CommonAI C.I.C.

<div>CommonAI CIC is a non-profit membership organisation, founded on a belief in collaborative engineering for the safe and responsible development of foundational AI technologies. A place where AI startups, enterprises large and small, public sector bodies and academia can share resources and knowledge, to codevelop and grow businesses, fast.
We are led by experienced founders, investors and engineers who believe that collaborative engineering drives faster AI innovation and are backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems.
The Opportunity
We're seeking a highly skilled Software Engineer to work on Panopticon, a new AI framework equipped with stringent control and compliance protocols. Aimed primarily at highly regulated sectors such as financial services and healthcare, Panopticon is a core component of our High Assurance programme. It is designed to enable AI systems to be used safely in high-risk environments where accuracy, explainability, and accountability are a hard requirement.
Panopticon is written in Rust, leveraging its memory safety and performance characteristics to build a robust, secure infrastructure that provides mathematical proof of correct outputs, sandboxed execution, and intelligent filtering.
As an AI-first company, we strongly believe in collaborative engineering powered by the tools we are helping to build. This role places a major emphasis on using LLMs, AI coding assistants, and autonomous agents for software development.
What You'll Do<ul><li>
Design, build, and maintain core components of the Panopticon framework using idiomatic Rust.</li><li>
Develop secure execution environments, multi-model validation pipelines, and intelligent filtering systems to prevent data leakage and policy violations.</li><li>
Extensively utilise LLMs, AI agents, and advanced coding copilots to write, test, and refactor code, actively seeking ways to accelerate feature development and deployment without compromising on quality.</li><li>
Architect systems that integrate safely with foundation models and user environments, ensuring strict compliance and governance frameworks are adhered to.</li><li>
Review AI-generated code for security, performance, and correctness, establishing CI/CD pipelines optimised for AI-assisted workflows.</li><li>
Collaborate with CommonAI&rsquo;s members to translate theoretical compliance protocols into production-ready software.</li></ul> 

Requirements 
<ul><li>
Proven experience building systems in Rust and familiarity with the ecosystem&rsquo;s best practices.</li><li>
Strong understanding of software architecture, systems programming, and secure coding practices.</li><li>
Direct experience and high proficiency in using LLMs and AI agents for software development (e.g., prompt engineering for code generation, experience with tools like Cursor, GitHub Copilot, or bespoke autonomous agents for code review and iterative development).</li><li>
Familiarity with the challenges of deploying AI in enterprise environments (e.g., security vulnerabilities, regulatory risk, auditability).</li><li>
Ability to debug complex software systems and optimise for latency, safety, and scalability.</li><li>
Strong problem-solving skills and a passion for redefining how software is written using AI.</li></ul>
We also value:<ul><li>
Background in highly regulated industries such as financial services, banking, or healthcare.</li><li>
Familiarity with formal verification, applied cryptography, or verifiable compute.</li><li>
Experience with sandboxing technologies (e.g., WebAssembly/Wasm, lightweight VMs, containers).</li><li>
Understanding of modern AI tooling, foundation model APIs, and deployment pipelines.</li><li>
Contributions to open-source Rust projects or AI development tools (please include links to relevant projects, GitHub repositories, or technical blogs in your application).</li></ul>
Ideally, you will have a background in building critical infrastructure, combined with a forward-looking mindset eager to push the boundaries of AI-assisted engineering. 
Benefits 
Benefits<ul><li>
A collaborative and supportive work environment</li><li>
The opportunity to have a high impact in a growing organisation</li><li>
Competitive salary package and pension</li><li>
Professional development opportunities</li><li>
Networking opportunities with influential people from across the tech sector, financial services, and academia</li><li>
A vibrant office environment located a few minutes' walk away from Cambridge train station</li></ul>
CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace.</div>

Software Engineer (Rust)

Roku

<div>
 Teamwork makes the stream work.
 
 &nbsp;
 
 
 Roku is changing how the world watches TV
 
 
 Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers.
 
 
 From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines.
 
 
 &nbsp;
 
 
 &nbsp;
 
 
 About the Team
 
 
 
 At Roku, the Device Monetization and Themed Experiences (DMTE) team, a part of the Advertising organization, is where the magic behind the scenes happens. We're the engineers who build the high-performance graphics and UI foundations that power the FRAME engine &mdash; the core technology enabling Roku's smooth, responsive, and visually rich experiences on millions of devices worldwide. Our work lives in the middleware and UI layers, and its impact is felt every time a user navigates a menu, enjoys an animated ad, or is wowed by the bespoke experience built to market the latest TV show or Movies. We thrive on solving the toughest technical challenges &mdash; from optimizing UI rendering to fine-tuning memory usage &mdash; using BrightScript (a JavaScript-like language) to deliver rock-solid, high-performance solutions. We work in a collaborative, high-trust environment where great ideas can come from anywhere, partnering closely with firmware, UI, and product teams to ensure our platform is lightning fast, reliable, and ready for the next generation of streaming innovation. If you love building the invisible foundations that make great user experiences possible, this is the team for you.
 
 
 
 About the Role
 
 
 As a Senior Agentic AI Engineer in the DMTE team, you'll be the driving force behind embedding intelligent, autonomous AI capabilities into Roku's platform &mdash; reimagining how our systems create, optimize, and deliver experiences to tens of millions of devices. Rather than building UI features directly, you'll design and deploy agentic AI systems that reason, plan, and act across our development and delivery pipelines &mdash; from automating the generation of themed experiences to enabling self-optimizing rendering workflows within the FRAME engine. You'll leverage your years of experience in software engineering and building world class UI to build AI agents that understand the constraints of embedded, performance-critical systems and operate effectively within them. This is a role for engineers who think in terms of autonomous systems, multi-step reasoning, and tool-use architectures &mdash; and who want to fundamentally reshape how a streaming platform is built, maintained, and evolved.
 
 
 What You'll Be Doing
 
 <ul>
 <li>
 We don't train models, we don't 'fine-tune' LLMs; We build automated agentic processes
 </li>
 <li>
 Design, build, and deploy agentic AI systems that autonomously generate, test, and optimize BrightScript/TypeScript code and UI experiences for the FRAME engine
 </li>
 <li>
 Architect multi-agent workflows (planning, tool-use, retrieval, execution, validation) that accelerate development and reduce manual engineering effort across the team
 </li>
 <li>
 Develop AI-powered automation that understands the constraints of embedded C++ environments and produces performance-safe, memory-efficient outputs
 </li>
 <li>
 Build and maintain evaluation frameworks to measure agent reliability, accuracy, and performance in production-critical contexts
 </li>
 <li>
 Collaborate with cross-functional teams (firmware, UI, product) to identify high-impact opportunities for AI-driven automation and intelligent tooling
 </li>
 <li>
 Stay at the forefront of agentic AI research &mdash; including LLM orchestration, RAG, function calling, and autonomous code generation &mdash; and bring those advances into our platform
 </li>
 <li>
 Mentor engineers across the team on AI-first development practices and help establish best practices for human-agent collaboration
 </li>
 </ul>
 
 &nbsp;
 
 
 &nbsp;
 
 
 We're Excited if you Have
 
 &nbsp;
 <ul>
 <li>
 Proven experience building agentic AI systems that generate, optimize, and deliver scalable applications in production environments
 </li>
 <li>
 Strong software engineering foundation with a track record of shipping reliable, performant systems at scale
 </li>
 <li>
 Deep familiarity with modern LLM orchestration tools, prompt engineering techniques, and AI/ML frameworks
 </li>
 <li>
 Experience with retrieval-augmented generation (RAG), function/tool calling, and evaluation-driven development for AI agents
 </li>
 <li>
 A builder's mentality &mdash; you don't just use AI tools, you create autonomous systems that multiply the impact of entire teams
 </li>
 <li>
 Proficiency in TypeScript (or similar languages) and Python for agent development, scripting, and pipeline automation
 </li>
 <li>
 A software engineer's instinct for reliability, testability, and clean architecture &mdash; applied to the unique challenges of non-deterministic AI systems
 </li>
 <li>
 Excellent technical communication, root cause analysis abilities, and a proactive mindset with passion for fast iteration
 </li>
 </ul>
 
 &nbsp;
 
 
 &nbsp;
 
 
 Our Hybrid Work Approach
 
 
 Roku fosters an inclusive and collaborative environment where teams work in the office Monday through Thursday. Fridays are flexible for remote work except for employees whose roles are required to be in the office five days a week or employees who are in offices with a five day in office policy.
 
 
 &nbsp;
 
 
 Benefits
 
 
 Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs. It's important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter.
 
 
 &nbsp;
 
 
 Accommodations
 
 
 Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to EmployeeRelations@Roku.com.
 
 
 &nbsp;
 
 
 The Roku Culture
 
 
 Roku is a great place for people who want to work in a fast-paced environment where everyone is focused on the company's success rather than their own. We try to surround ourselves with people who are great at their jobs, who are easy to work with, and who keep their egos in check. We appreciate a sense of humor. We believe a fewer number of very talented folks can do more for less cost than a larger number of less talented teams. We're independent thinkers with big ideas who act boldly, move fast and accomplish extraordinary things through collaboration and trust. In short, at Roku you'll be part of a company that's changing how the world watches TV.
 
 
 We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002.
 
 
 To learn more about Roku, our global footprint, and how we've grown, visit https://www.weareroku.com/factsheet.
 
 
 By providing your information, you acknowledge that you want Roku to contact you about job roles, that you have read Roku's Applicant Privacy Notice, and understand that Roku will use your information as described in that notice. If you do not wish to receive any communications from Roku regarding this role or similar roles in the future, you may unsubscribe at any time by emailing WorkforcePrivacy@Roku.com.
 
</div>

Senior Agentic AI Engineer

Flagship Pioneering, Inc.

<div>Position Summary:

We are looking for a Machine Learning Scientist to build AI and machine learning systems that turn complex biological data into actionable scientific insight. You will work at the intersection of ML, genomics, causal biology, and target discovery. The role includes building models, agentic AI workflows, systems that help automate analysis, reasoning, and decision support, and AI assisted tools that help connect genotype, cell state, perturbation, phenotype, and disease mechanism. This is a hands-on role for someone who enjoys writing clear, reliable code, uses modern AI tools to move faster, and wants their work to shape real biological and therapeutic decisions.

Responsibilities:
<ul>
<li>Build ML models for genomic, single-cell, perturbation, and phenotype data.</li>
<li>Develop agentic AI workflows that help scientists analyze data, test hypotheses, and make better decisions.</li>
<li>Use AI coding tools to accelerate development while keeping code reliable, readable, tested, and reproducible.</li>
<li>Train and fine tune foundation models, language models, and representation learning methods for target discovery.</li>
<li>Model relationships between genotype, cell state, perturbation response, causal biology, and disease.</li>
<li>Collaborate closely with computational scientists, experimental biologists, software engineers, and target discovery teams.</li>
<li>Communicate results clearly, including model assumptions, limitations, and next steps.</li>
</ul>
Qualifications:

You do not need to meet every item to apply. Strong candidates may come from academia, industry, open-source work, or hands-on research.
<ul>
<li>PhD, Master's degree, or equivalent experience in machine learning, computer science, computational biology, genomics, bioinformatics, statistics, engineering, or a related field.</li>
<li>Strong Python coding skills and experience building practical Deep Learning ML systems.</li>
<li>Experience using AI coding tools, coding assistants, LLM-based workflows, or agentic development tools.</li>
<li>Experience training, evaluating, or applying ML models to complex real-world data.</li>
<li>Depth in one or more of: biomedical foundation models, agentic AI, Perturb-seq, single-cell genomics, genotype&ndash;phenotype modeling, causal inference, perturbation modeling, or large-scale biological datasets.</li>
<li>Evidence of technical depth through papers, thesis work, open-source projects, industry projects, or substantial hands-on applied research.</li>
</ul>
Values and Behaviors:
<ul>
<li>Encourage respectful disagreement and cultivate open-minded, ego-free interactions to continuously push each other towards excellence</li>
<li>Seek out diverse perspectives; practice active listening and genuine curiosity to ensure all contributions are valued, regardless of source</li>
<li>Recognize the impact of your behavior, language and attitudes, and strive for balanced, meaningful exchanges that enhance mutual growth and understanding in all interactions</li>
<li>Use a company-first mindset to guide decision-making; prioritize team over individual success</li>
<li>Take calculated risks and challenge convention in the quest for exceptional outcomes</li>
</ul>
About Quotient:

Quotient Therapeutics is a privately-held, early stage company developing breakthrough medicines informed by natural somatic genetic diversity present in patients. Through our work in somatic genomics, we are forging a new status quo for biopharma research and development across a broad pipeline of internal and partnered programs.

The company was founded by Flagship Pioneering, an innovative enterprise that conceives, creates, resources, and grows first-in-category life sciences companies. Flagship Pioneering has created over 100 groundbreaking companies over the past twenty years, all of which are pioneering novel and proprietary biological, industrial, and engineering approaches to solve major needs in human health and sustainability. These companies include Moderna (MRNA), Generate Biomedicines, Sana Biotechnology (SANA), Tessera Therapeutics, Evelo Biosciences (EVLO), Indigo Agriculture, Seres Therapeutics (MCRB), and Syros Pharmaceuticals (SYRS).

Quotient Therapeutics and Flagship Pioneering are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Recruitment &amp; Staffing Agencies:

Quotient Therapeutics (&quot;Quotient&quot;) and Flagship Pioneering (&quot;FSP&quot;) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Quotient, FSP or their employees is strictly prohibited unless contacted directly by Flagship Pioneering's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.<div> 

Privacy Notice for Applicants: When you apply for a role at Flagship Pioneering or one of its portfolio companies, we collect and use personal information you provide (such as your name, contact details, work history, and application materials) to evaluate your application, communicate with you, and comply with legal obligations. Your application data is processed through Greenhouse, our applicant tracking system, and may also be reviewed using AI-assisted screening tools. We do not sell your personal information. California residents have rights under the CCPA/CPRA including to know, delete, and opt out of the sharing of their personal information. If you are located in the EU or UK, we process your data under GDPR and you have rights to access, rectify, and erase your data. To exercise your rights or for questions, contact privacy@flagshippioneering.com.</div></div>

Senior Machine Learning Scientist

Graphcore

<div><h3 class="jobSectionHeader">About the job</h3>

Help prove the ML software stack that future AI systems will depend on. Graphcore is expanding the software systems behind AI compute at datacenter scale. This role focuses on validating a complex machine learning stack before it reaches customers and hardware.You will build the test infrastructure, automation and tooling that engineers trust every day. Your work will help raise reliability, performance and maintainability across frameworks, simulators, emulators and future hardware. You will shape test architecture across large codebases, CI pipelines and representative ML workloads. You will use strong software engineering judgement to turn complex technical goals into scalable validation systems.

This is a role for someone who enjoys depth, ownership and useful engineering. You will make quality easier, faster and more visible for teams building at the edge of AI compute.
<h3 class="jobSectionHeader">
The team and culture</h3>

The ML QA team sits where Graphcore's software components come together. Engineers work across unit tests, integration tests, full model runs, subgraph validation and benchmarking.

Work is organised through focused squads with clear ownership. People are expected to step up, speak openly and improve how the team builds, tests and learns.

Decisions are grounded in evidence from code, data and system behaviour. The team works closely with software teams to identify gaps, improve tooling and move priorities forward quickly.
<h3 class="jobSectionHeader">
What we're looking for</h3>
<ul><li>Strong software design skills, with experience building maintainable systems across large codebases.</li><li>Production Python experience, including testable, reliable code used by other engineers.</li><li>Experience with CI/CD, automated testing and Linux based development workflows.</li><li>Familiarity with C or C++, with confidence reading and debugging low level code.</li><li>Understanding of ML frameworks, workloads or model execution beyond simple API usage.</li><li>Ability to mentor engineers, improve practices and take ownership of complex technical problems.</li></ul>
<h3 class="jobSectionHeader">
Benefits</h3>
<ul><li>Unlimited annual leave</li><li>Up to 5% matched pension</li><li>Phantom equity &ndash; share in Graphcore's success</li><li>True flexibility in how and where you work</li><li>Office spaces designed for collaboration</li><li>Free food and an on-site barista</li><li>Health cash plan</li><li>Income protection</li><li>Life assurance</li><li>Along with other benefits you can choose from (private medical insurance, dental plan etc)</li></ul>
We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work.

We're an equal opportunity employer and recognise that everyone brings different strengths and perspectives. If you need any adjustments during the interview process, just let us know - we're happy to support you.
<h3 class="jobSectionHeader">
Join the team at Graphcore</h3> 

Graphcore is one of the world's leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry.

As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world's most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone.

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If you want to shape how complex ML software is tested, trusted and improved, we'd love to hear from you. Apply now to be part of the journey.</div>

Senior Software Engineer (ML QA)

<div>Arm's Vulnerability Research Tooling Team is looking for a Principal Software Engineer to help build AI-enabled tooling for hardware security issue identification.
You will help design, build, and evolve systems that capture hardware security expertise and turn it into reusable datasets, analysis workflows, evaluation methods, and tooling.
This role sits at the intersection of software engineering, AI tooling, data engineering, and security. The focus is to compose software and AI solutions that help detect security concerns across architectural specifications, RTL, firmware interfaces, software models, and hardware-software design assumptions.
Job Overview:
We are seeking a Principal Software Engineer to play a meaningful role in establishing a new AI-enabled capability for hardware security issue identification.
Working closely with hardware security experts, software security engineers, research collaborators, and platform teams, the role is responsible for turning expert review knowledge into scalable software systems. You will help define how hardware security expertise is captured, structured, evaluated, and applied through AI-assisted analysis workflows.
This is not a traditional hardware validation or verification role. You do not need to be a hardware verification specialist. However, you should be comfortable building systems that help experts reason across architectural requirements, RTL, firmware connections, software representations, and hardware-software build assumptions.
As a Principal Engineer, you will be expected to create structure in an emerging area, influence technical direction, and help mature early prototypes into durable internal capabilities.
Responsibilities:<ul><li>
Lead the design and delivery of AI-enabled tooling for hardware security issue identification across specifications, RTL, firmware interfaces, software models, and hardware-software boundaries.</li><li>
Develop analysis workflows and services that combine AI, retrieval, static analysis, automation, and human review to produce credible security findings.</li><li>
Partner across hardware engineering, software security, research, fuzzing, threat modelling, and platform teams to ensure the tooling is practical, technically grounded, and aligned with engineering workflows.</li><li>
Define evaluation approaches for AI-assisted security analysis, including benchmark tasks, ground truth, confidence measures, false-positive handling, and evidence quality.</li><li>
Contribute to the long-term roadmap for hardware security AI tooling, including prototype evolution, productionisation, platform integration, and future research directions.</li></ul>
Required Skills and Experience :<ul><li>
Significant experience designing and building software systems using modern backend, data, platform, or developer tooling engineering practices.</li><li>
Experience building AI-enabled tooling, data-heavy engineering systems, analysis platforms, developer tools, or automation for complex technical domains.</li><li>
Practical understanding of LLM-based systems, including retrieval, embeddings, context engineering, structured outputs, tool/function calling, workflow orchestration, and AI-assisted analysis patterns.</li><li>
Familiarity with sophisticated AI workflow techniques such as agentic workflows, task decomposition, evaluator/critic loops, human-in-the-loop review, context or memory systems, and traceable evidence generation</li><li>
Ability to work with domain experts, extract tacit knowledge, and translate it into structured data, software workflows, evaluation criteria, and maintainable tooling.</li><li>
Ability to influence technical direction and collaborate effectively across security, software, hardware, research, and platform teams.</li></ul>
&ldquo;Nice To Have&rdquo; Skills and Experience :<ul><li>
Exposure to hardware architecture, RTL, firmware, SoC design, CPU/GPU systems, or hardware/software interfaces.</li><li>
Exposure to hardware security, platform security, vulnerability research, secure development, or threat modelling.</li><li>
Experience with static analysis, symbolic analysis, formal methods, or other automated techniques.</li><li>
Experience building datasets, benchmarks, evaluation harnesses, or test corpora for AI-assisted analysis.</li><li>
Familiarity with cloud, containerized development, infrastructure-as-code, CI/CD, observability, or internal engineering platforms.</li><li>
Experience collaborating with research teams or translating research ideas into production engineering workflows.</li></ul>
Accommodations at Arm
At Arm, we want to build extraordinary teams. If you need an adjustment or an accommodation during the recruitment process, please email accommodations@arm.com. To note, by sending us the requested information, you consent to its use by Arm to arrange for appropriate accommodations. All accommodation or adjustment requests will be treated with confidentiality, and information concerning these requests will only be disclosed as necessary to provide the accommodation. Although this is not an exhaustive list, examples of support include breaks between interviews, having documents read aloud, or office accessibility. Please email us about anything we can do to accommodate you during the recruitment process.
Hybrid Working at Arm
Arm&rsquo;s approach to hybrid working is designed to create a working environment that supports both high performance and personal wellbeing. We believe in bringing people together face to face to enable us to work at pace, whilst recognizing the value of flexibility. Within that framework, we empower groups/teams to determine their own hybrid working patterns, depending on the work and the team&rsquo;s needs. Details of what this means for each role will be shared upon application. In some cases, the flexibility we can offer is limited by local legal, regulatory, tax, or other considerations, and where this is the case, we will collaborate with you to find the best solution. Please talk to us to find out more about what this could look like for you.
Equal Opportunities at Arm
Arm is an equal opportunity employer, committed to providing an environment of mutual respect where equal opportunities are available to all applicants and colleagues. We are a diverse organization of dedicated and innovative individuals, and don&rsquo;t discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
<div>Salary Range:
&pound;126,200 <ul><li>&pound;170,800</li></ul> per year</div></div>

Principal Software Security Engineer

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