senior software engineer

ai engineer

senior data scientist

software engineer

lead software engineer

senior research engineer

DeepMind

<div><h3 class="jobSectionHeader">Minimum qualifications:</h3><ul>
<li>Bachelor's degree in Computer Science, Physics, Mathematics, Chemistry, Engineering, a related field, or equivalent practical experience.</li>
<li>5 years of experience in machine learning, engineering, and software development using Python.</li>
<li>Experience with data structures or algorithms in an academic or industry setting</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>PhD in a relevant scientific or computational field.</li>
<li>Experience in agentic AI and modern machine learning paradigms (e.g., diffusion, transformers, agentic tools, LLMs).</li>
<li>Knowledge of quantum computing concepts.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.

As a Research Engineer on our Science Team, you will contribute to our Quantum Computing Initiative. This role is an excellent opportunity for a creative and driven engineer who truly burns for the immense possibilities of AI for Science. 
 
In this role, you will act as the crucial bridge between research and implementation, by seamlessly linking quantum computing research with ML. As an amazing team player, you will collaborate with domain experts in (quantum) computer science, mathematics, computational chemistry, physics, and machine learning.
Artificial intelligence will be one of humanity&rsquo;s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.<div>
We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.</div></div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Deliver on complex research and engineering milestones, assuming end-to-end ownership of implementing and scaling ML solutions (traditional and agentic) at the intersection of quantum computing and machine learning.</li>
<li>Complement the algorithms development pillar by translating classical and quantum algorithms into robust code, balancing implementation time with efficiency, design simplicity, and sustainability.</li>
<li>Facilitate communication between research and engineering by advocating code readability, promoting engineering best practices, and writing effective design documents.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We 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. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Research Engineer, Quantum Computing, DeepMind

Anthropic

<div><div><h2 class="jobSectionHeader">About Anthropic</h2>

Anthropic&rsquo;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.</div><div><h2 class="jobSectionHeader">
About the role</h2>

Anthropic's RL Scaling Science team studies how reinforcement learning behaves as we scale it (across model size, compute, and task horizon) and turns that understanding into the training recipes behind our frontier models. As a Research Engineer on this team, you'll design and run large-scale experiments to understand and resolve bottlenecks, build the benchmarks that make long-horizon progress measurable, and ship validated findings directly into production training.

This role lives at the boundary between research and engineering. The problems are open, the experiments run at frontier scale, and the path from a robust result to production is short.
<h2 class="jobSectionHeader">
Key responsibilities</h2>
<ul><li>Design, run, and interpret large-scale RL experiments, reasoning rigorously about what the data does and doesn't show</li>
<li>Investigate how RL improves as horizon, compute, and model size grow</li>
<li>Build and maintain benchmarks for long-horizon RL so progress is measurable and reproducible</li>
<li>Translate validated findings into production training recipes, exercising judgment about when a result is robust enough to ship</li>
<li>Debug complex issues at the seam where research meets infrastructure - failures that only appear at scale</li>
<li>Partner closely with adjacent RL teams across research and engineering and advance our overall RL stack</li>
</ul><h2 class="jobSectionHeader">Minimum qualifications</h2>
<ul><li>Strong empirical research skills in Reinforcement Learning, large-scale ML training, or a closely adjacent area</li>
<li>Demonstrated ability to own large experiments end-to-end, from design through interpretation</li>
<li>Proficiency in Python and experience working with large-scale or distributed ML systems</li>
<li>Comfort operating at the research/systems boundary, including debugging where the two meet</li>
<li>Care about the societal impacts of AI and responsible scaling</li>
</ul><h2 class="jobSectionHeader">Preferred qualifications</h2>
<ul><li>Published or shipped work in long-horizon RL or RL fundamentals</li>
<li>Experience translating research findings into production training recipes</li>
<li>Demonstrated large scale industry impact via RL interventions</li>
<li>Experience working on frontier-scale training runs with long trajectories</li>
</ul><h2 class="jobSectionHeader">Representative projects</h2>
<ul><li>Design a benchmark suite for long-horizon RL that distinguishes genuine capability gains from artifacts of evaluation setup</li>
<li>Take a promising experimental finding, stress-test it across model scales, and work with training teams to land it in a production recipe</li>
<li>Investigate an unexpected scaling trend in an RL run and trace it to a root cause spanning algorithm, data, and infrastructure</li></ul></div><div><div><div><div> 
The annual compensation range for this role is listed below.

For sales roles, the range provided is the role&rsquo;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</div></div>
Annual Salary:
&pound;375,000 - &pound;640,000 GBP</div></div><div><h2 class="jobSectionHeader">
Logistics</h2>

Minimum education: Bachelor&rsquo;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&mdash;visit anthropic.com/careers directly for confirmed position openings.
<h2 class="jobSectionHeader">
How we're different</h2>

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 &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; 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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
<h2 class="jobSectionHeader">
Come work with us!</h2>

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.</div></div>

Research Engineer, RL Scaling Science

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

Resolution

<div><h1 class="jobSectionHeader">About Resolution</h1>
Resolution does research on how to align artificial superintelligence (ASI). ASI may be developed in the next few years, but it is unclear whether alignment is on track to be ready in the same timeframe. We aim at higher a priori confidence in aligned outcomes by pursuing a portfolio of theory and empirics bets, any one of which &mdash; if it succeeds &mdash; would meaningfully advance the field. We invest heavily in research automation to accelerate progress, and we believe that stronger alignment theory unlocks higher automation: more principled approaches give us better filters for which directions of automated research are promising.
Resolution was founded in 2026 by researchers from UK AISI's Alignment Team, who ran the &pound;30m Alignment Project, and Timaeus, who pioneered applying singular learning theory to alignment.
For more information, see our announcement.<h1 class="jobSectionHeader">
About the Team</h1>
We are hiring Research Engineers across several main focus areas. We expect the boundaries between these areas to be flexible, but please indicate which mode you're more interested in (or &quot;either&quot;) in your application.
Research Automation (primary focus). A cross-cutting function that builds the infrastructure and tooling our researchers use to scale their work, increasingly leveraging fleets of AI research assistants alongside small teams of humans.
Program-embedded Research Engineering (also hiring). Research engineers embedded within one of our research programs (scalable oversight, complexity theory, learning theory, personas, and possible future programs like heuristic arguments or game theory), partnering with researchers on scaling experiments, building program-specific infrastructure, and translating theoretical insights into empirical tools.<h2 class="jobSectionHeader">
About the Role</h2>
Research Engineers at Resolution are core members of our research teams, directly driving both research and the core infrastructure behind it. We believe clean engineering on automation, experimentation, and infra is essential to ambitious research, and that excellence on this front requires active research participation.<h2 class="jobSectionHeader">
Responsibilities</h2><ul><li>
(Research automation track) Build agentic research infrastructure: experiment orchestration, hypothesis generation, automated analysis pipelines; autoformalization tooling for the theory side; internal AI-powered tools for researchers</li><li>
(Program-embedded track) Scale program experiments to frontier-tier models; build program-specific infrastructure; partner with researchers on engineering and implementation.</li><li>
(Both) Maintain and extend distributed training, experiment, and evaluation infrastructure</li><li>
(Both) Contribute to and maintain shared codebases across the org</li><li>
(Both) Communication of engineering &amp; automation progress, obstacles &amp; learnings to your team and the wider org via Slack and in weekly meetings.</li></ul>
We're on the lookout for excellence, so if you're a cracked engineer who doesn't precisely fit these descriptions, please still apply!<h2 class="jobSectionHeader">
You May Be a Good Fit If You</h2><ul><li>
Have a strong software engineering background, including production-quality Python</li><li>
Have deep experience with ML frameworks (PyTorch or Jax) and distributed-training stacks</li><li>
Have a demonstrated ability to ship complex systems end-to-end</li><li>
Have a Bachelor's degree or equivalent in CS, physics, math, ML, or related</li><li>
Are willing to use AI tools aggressively in your own workflow, with appropriate care to not get fooled!</li><li>
Are motivated by alignment of artificial superintelligence (ASI) and want to contribute to it full-time.</li></ul><h2 class="jobSectionHeader">
Strong Candidates May Also Have</h2><ul><li>
Experience with autoformalization, Lean, or other proof-assistant tooling</li><li>
Background in research infrastructure or ML platform engineering at frontier labs</li><li>
Experience scaling ML systems to 100B+ parameter scale</li><li>
Experience with CUDA kernel development or GPU optimization</li><li>
Familiarity with alignment research</li></ul><h1 class="jobSectionHeader">
Application Process</h1>
Initial screener. A 20-minute conversation with a senior researcher to discuss your research background, motivations, and interests.
Work trial. A 4-hour take-home assignment. We'll collect references in parallel. We'll compensate you for your time, subject to right-to-work constraints.
Work trial review. A 45-minute discussion of your work trial.
Research talk. A 30&ndash;40 minute interactive conversation about your previous research.
Senior 1:1. A 30-minute conversation with a member of our research leadership.<h1 class="jobSectionHeader">
Logistics</h1>
Salary: Your salary depends on the scope, autonomy, and impact we expect you to have while working at Resolution. The expected range of salaries for this role is:<ul><li>
L3 (SWE I): $141,000 remote; $236,000 in-person</li><li>
L4 (SWE II): $208,000 remote; $346,000 in-person</li><li>
L5 (Senior SWE): $270,000 remote; $451,000 in-person</li><li>
L6 (Staff SWE): $402,000 remote; $670,000 in-person</li><li>
L7 (Senior Staff SWE): $738,000 remote; $930,000 in-person</li></ul>
Strong early-career engineers will typically come in at L3. Someone with significant independent research engineering experience would likely start at L4 or L5.
Location: Berkeley, California. Remote may be considered in exceptional cases.
Benefits:<ul><li>
5 weeks of paid vacation per year, in addition to public holidays.</li><li>
Comprehensive healthcare insurance (medical, dental, vision).</li><li>
Unlimited sick leave to prioritize your well-being.</li><li>
An unconditional 401(k) contribution equal to 4% of your salary.</li></ul>
Visa sponsorship: We can sponsor visas for relocation to Berkeley.
Minimum education: A bachelor's degree in a field relevant to the role, or an equivalent combination of education, training, and/or professional experience that demonstrates comparable knowledge.
Deadline: Applications are rolling &mdash; please apply ASAP. We'll respond to applications within one week of receipt.
Start date: ASAP.
Compensation Range: $141K - $930K</div>

Research Engineer

venkatesh.j@terralogic.com

At Terralogic Solutions Inc., we bridge the gap between complex infrastructure and seamless deployment. We are looking for a visionary Senior DevOps Specialist who views infrastructure as code and development pipelines as an art form. If you thrive on optimizing delivery cycles, automating everything move-able, and building bulletproof deployment systems, you will fit right in.What You Will Do<ul><li>Architect and advance robust CI/CD pipelines with heavy focus on Jenkins.</li><li>Streamline software delivery by automating complex build and release processes.</li><li>Collaborate with global engineering teams to improve system reliability.</li><li>Maintain infrastructure scalability while troubleshooting deployment bottlenecks.</li><li>Innovate security integrations directly into our automated workflows.</li></ul>What You Bring<ul><li>Experience: 5+ years of dedicated DevOps engineering experience in production environments.</li><li>Jenkins Mastery: Mandatory, deep expertise in Jenkins development, pipeline-as-code, and plugin management.</li><li>Location: Physically located in the United Kingdom (London preferred, but open to any UK location).</li><li>Work Authorization: Full, pre-existing legal right to work in the UK without requiring employer visa sponsorship.</li><li>Tech Stack Skills: Strong proficiency in cloud infrastructure, containerization, and configuration management tools.</li></ul>Why You Will Love Working Here<ul><li>True Remote Freedom: Work from anywhere in the UK with a schedule built around trust and output.</li><li>London Connectivity: Option to connect with local team members if you are based in or near the capital.</li><li>Impact &amp; Ownership: Lead the charge on our automation strategy with the autonomy to implement your ideas.</li><li>Continuous Growth: Access to cutting-edge technologies and support for professional certifications.</li></ul>Pay: &pound;70,000.00-&pound;90,000.00 per yearApplication question(s):<ul><li>Please mention your salary requirement</li><li>How soon can you join if we offer a position</li><li>Are you willing to take on this job through a consulting agreement with a USA-based entity?</li></ul>Experience:<ul><li>DevOps: 5 years (required)</li></ul>Language:<ul><li>English (required)</li></ul>Work authorisation:<ul><li>United Kingdom (required)</li></ul>Location:<ul><li>London, Greater London (preferred)</li></ul>Work Location: Remote

Senior Design Engineer

Elsevier

<div>Senior Software Engineer I &ndash; Search and AI Platform
Are you passionate about building scalable, high-performance data-driven applications?
 
Do you enjoy turning complex datasets into robust, reliable systems that deliver real business impact? 
 
About the team:
The Search and AI Platform is Elsevier&rsquo;s agentic data platform, which powers products such as LeapSpace, Scopus, ScienceDirect, Clinical Key, Reaxys, and our next-generation AI powered search systems. The platform uses agentic services to interrogate our rich knowledge graphs, search and recommendation systems, and our unparalleled collection of research data to deliver insights to the scientific community so they can collaborate more effectively, work smarter, and deliver quality research more quickly.
We are looking for an innovative, passionate Senior Software Engineer II to work as part of the teams building and enhancing our platform to deliver intelligent, scalable solutions that create real value for our clients.
About the role:
The Shared Graph Team is a core part of Elsevier&rsquo;s Search and AI Platform . This team builds structured queries based on relationships and entity metadata hydration, enabling advanced traversal, discovery, and recommendation systems. As a Senior Software Engineer II , you will work with a passionate team that delivers scalable, reliable, and innovative solutions that accelerate scientific discovery.
Key responsibilities:
<ul><li>Design and implement graph-based search services.
</li><li>Develop applications using Java , Spring Boot, Spring, GraphQL , and GraphQL Federation .
</li><li>Integrate with databases, web services, or AWS services (Neo4j, DynamoDB, RDS, S3, Parameter Store, SQS, SNS, Kinesis) to support ingestion, storage, and messaging pipelines.
</li><li>Champion clean code, SOLID principles, and engineering best practices , setting standards and mentoring engineers.
</li><li>Collaborate with product managers and engineering teams to deliver advanced search and recommendation features.
</li><li>Ensure robust monitoring and logging with New Relic and Coralogix , driving reliability and performance.
</li></ul>Requirements:
<ul><li>4+ years of professional software engineering experience in distributed systems or search platforms .
</li><li>Proven track record building scalable backend systems and APIs.
</li><li>Strong expertise in Java and the Spring Boot ecosystem .
</li><li>Hands-on experience with GraphQL API/REST APIs design.
</li><li>Solid background in cloud-native architectures with AWS and Kubernetes (EKS) .
</li><li>An advocate of best practices for rapid development of quality software, including SOLID principles, clean code, architectural design patterns, CI/CD
</li><li>Familiarity with Agile, Kanban, or other iterative development methodologies.
</li><li>Comfortable learning new technologies, languages, and tools on the job, to ensure that the product is not left behind in a rapidly evolving ecosystem
</li><li>An inclusive, positive, collaborative mindset and a desire to deliver real business value to our customers
</li></ul>Nice to have:
<ul><li>Experience with Apollo Router or advanced GraphQL federation strategies.
</li><li>Background in data modelling for graph-based systems .
</li><li>Familiarity with search platforms or AI-driven discovery systems.
</li><li>Experience working in high-throughput, distributed systems
</li></ul>Why join us?
Join our team and contribute to a culture of innovation, collaboration, and excellence. If you are ready to advance your career and make a significant impact, we encourage you to apply.
Work in a way that works for you 
 
We promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous wellbeing initiatives and shared parental leave, we will help you meet your immediate responsibilities and your long-term goals.
<ul><li>Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
</li></ul>Working for you
We know that your well-being and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
<ul><li>Comprehensive Pension Plan
</li></ul><ul><li>Generous vacation entitlement and option for sabbatical leave
</li></ul><ul><li>Maternity, Paternity, Adoption and Family Care leave
</li></ul><ul><li>Flexible working hours
</li></ul><ul><li>Personal Choice budget
</li></ul><ul><li>Internal communities and networks
</li></ul><ul><li>Various employee discounts
</li></ul><ul><li>Recruitment introduction reward
</li></ul><ul><li>Employee Assistance Program (global) 
</li></ul> 
About the business &ndash;
A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world&rsquo;s grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.
If performed in NLD Amsterdam (Radarweg), the base pay range is &euro;86,900 - &euro;144,600.This job may be subject to a collective labor agreement in the Netherlands. Please consult with the hiring team for further details.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here .
Please read our Candidate Privacy Policy .
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
USA Job Seekers:
EEO Know Your Rights .</div>

Senior Software Engineer I – Search and AI Platform

Graphcore

<div>
 
 About The Job
 
 
 
 Validate the ML stack that turns accelerator hardware into trusted AI performance.
 
 
 This role sits where modern ML models meet Graphcore&rsquo;s software and hardware stack. You will test, benchmark and validate complex systems before they reach customers.
 
 
 Your work will expose regressions, correctness issues and performance limits across frameworks, models and execution environments. You will help teams understand what is working, what is breaking and why.
 
 
 You will run open source models, build automated benchmarking pipelines and create targeted tests for low level ML behaviour. That includes numerical precision, quantisation, attention mechanisms, distributed execution and model subgraphs.
 
 
 This is a role for someone who wants to stay close to how AI systems really work. You will not design new models, but you will make them run reliably on ambitious infrastructure.
 
 
 The team and culture
 
 
 The ML QA team is where Graphcore&rsquo;s ML software stack comes together for validation. Work spans unit tests, full model benchmarks, distributed workloads, simulators, emulators and hardware targets.
 
 
 Engineers are expected to take ownership, question assumptions and improve how testing is done. The team moves quickly, but decisions are grounded in evidence, benchmark data and technical discussion.
 
 
 You will work closely with software, infrastructure and hardware teams. Squads organise around priorities, with space for engineers to shape roadmaps and raise the quality bar.
 
 
 What we&rsquo;re looking for
 
 
 <ul>
 <li>
 Strong experience in Machine Learning or ML-adjacent software engineering roles.
 </li>
 <li>
 A solid grasp of neural networks, training, inference, numerical precision and performance trade-offs.
 </li>
 <li>
 Hands-on experience with PyTorch, TensorFlow, JAX, Triton or similar ML frameworks and tools.
 </li>
 <li>
 Strong Python skills for automation, experimentation, benchmarking and reporting.
 </li>
 <li>
 Experience designing, running and analysing ML benchmarks or model experiments.
 </li>
 <li>
 Confident debugging skills in Linux, with curiosity about model behaviour and system performance.
 
 
 </li>
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 Benefits
 
 
 
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 Unlimited annual leave
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 Up to 5% matched pension
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 Phantom equity &ndash; share in Graphcore&rsquo;s success
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 True flexibility in how and where you work
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 Office spaces designed for collaboration
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 Free food and an on-site barista
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 Health cash plan
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 Income protection
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 Life assurance
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 Along with other benefits you can choose from (private medical insurance, dental plan etc)
 
 
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 We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work.
 
 
 We&rsquo;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&rsquo;re happy to support you.
 
 
 Join the Team at Graphcore
 
 
 Graphcore is one of the world&rsquo;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&rsquo;s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone.
 
 
 Graphcore&rsquo;s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore brings together deep expertise to solve complex problems and deliver meaningful progress in AI compute.
 
 
 If you want to validate the systems behind next generation AI compute, we&rsquo;d love to hear from you. Apply now to help build what comes next.
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Senior Engineer (ML Engineer)

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