ai ml engineer

C-Serv

<div><p>Most engineers get to use large language models. You will get to build the systems that run them in production, at scale, under real latency and reliability constraints, for one of the most recognised names in application security and traffic management.</p><p>
Our client is expanding its AI Core group and is looking for a Senior or Staff AI &amp; ML Engineer in the UK. This is hands-on, build-focused work at the centre of how the business turns generative AI from a prototype into a dependable product. You will design and ship multi-agent systems, retrieval-augmented generation pipelines, anomaly detection, fine-tuned models, and the real-time inference layer that serves them.</p><p>
If you want ownership over a serving stack rather than a single notebook, and you want your work measured by what holds up in production rather than what demos well, this is the seat.</p>
What you will own<ul><li>Building and shipping generative AI features end to end: from model selection and fine-tuning through to the inference path that serves them.</li><li>Designing multi-agent and RAG architectures, and anomaly detection, that are accurate, observable, and cost-aware at scale.</li><li>Owning the real-time inference layer on Triton and TensorRT, optimising for latency, throughput, and GPU efficiency.</li><li>Standing up the surrounding microservices in Python and FastAPI, containerised and orchestrated for reliability.</li><li>Setting the technical bar: making architecture decisions, raising code quality, and mentoring engineers around you.</li><li>Partnering with research and product teams to take ideas from experiment to a service customers depend on.</li></ul><b><br>
Requirements</b><ul><li><br>
5 to 10 years of relevant experience, including a proven track record as a technical lead who mentors others.</li><li>Strong, current Python engineering, with production services built and shipped (FastAPI or similar).</li><li>Genuine hands-on GenAI depth: LLMs, RAG, agentic or multi-agent workflows, anomaly detection, and fine-tuning (for example LoRA or PEFT).</li><li>Real-time inference experience with NVIDIA Triton and TensorRT, with real attention to latency, throughput, and cost.</li><li>A microservices mindset, with services built in Python and FastAPI, containerised and orchestrated for reliability.</li><li>Solid grounding in Docker and Kubernetes, and large-scale distributed systems on a major cloud.</li><li>Right to work in the UK. We welcome applications from all backgrounds and are committed to equal opportunity.</li></ul>
Nice to have<ul><li>Experience with vLLM or other serving frameworks alongside Triton and TensorRT.</li><li>Experience in security, networking, or other high-reliability domains.</li><li>Big-data tooling (Spark, Databricks, Snowflake) and modern MLOps practice.</li></ul>
What you will get<ul><li>A genuine build mandate inside an established AI Core team, not a proof-of-concept that never ships.</li><li>Fully remote working anywhere in the UK, built around delivery rather than presence.</li><li>Competitive salary, strong benefits, and clear scope to grow into staff and principal-level influence.</li><li>The backing of C-Serv throughout: a delivery partner that runs a real quality filter and looks after its people, end to end.</li></ul><b><br>
Benefits</b><ul><li><br>
Fully remote working anywhere in the UK, built around delivery rather than presence.</li><li>A clear path to grow into staff and principal-level technical influence.</li><li>Full support from C-Serv across the hiring process and beyond, with full-cycle accountability.</li><li>A values-led, woman-owned delivery partner built on empathy, integrity, collaboration, and growth.</li></ul></div>

AI/ML Engineer

Xelix

<div>
 <strong>
  About Us
  <br/>
  <br/>
 </strong>
 At Xelix, we work with some of the world&rsquo;s largest companies to automate and strengthen their financial controls. Our AI solutions redefine how Accounts Payable teams operate &ndash; moving from manual processes to automated, intelligent workflows.
 <br/>
 <br/>
 Xelix is a fast-paced scale-up &ndash; things move fast and expectations are high. We raised our Series B with Insight Partners in June 2025 and are expanding aggressively. We have a team
 <strong>
  150
 </strong>
 talented people pulling together to achieve our goals. Everyone is trusted to take ownership, move fast and have a meaningful impact. We prioritise personal and professional growth, keep things fun, and love to celebrate a milestone together.
 <br/>
 <br/>
 In this role you&rsquo;ll grow, be challenged and help shape the future of Xelix. If you&rsquo;re excited about building something special with us, we&rsquo;d love to hear from you.
 <br/>
 <br/>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 We are hiring an AI Engineer to join our growing AI Engineering team. You&rsquo;ll design and build production AI systems &mdash; combining machine learning, large language models, and strong engineering &mdash; to solve real problems across documents, email, and financial data.
 <br/>
 <br/>
 We focus on building systems that work reliably in production, not just prototypes. We use modern AI tools extensively in our workflow, enabling engineers to operate at a higher level &mdash; focusing on system design, product thinking, and solving complex problems.
 <br/>
 <br/>
 <strong>
  What You'll Be Doing
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   AI Systems &amp; Agents: design and build production AI systems &mdash; including agent-based workflows, tool use, and multi-step reasoning.
  </li>
  <li>
   Model Development &amp; Adaptation: develop and improve models across text, vision, and structured data, including fine-tuning and hybrid ML + LLM approaches.
  </li>
  <li>
   LLM Platform Work: work with hosted and self-hosted models, contributing to decisions around model selection, performance, and cost.
  </li>
  <li>
   Production Engineering: write clean, maintainable Python and contribute to scalable, observable systems.
  </li>
  <li>
   Evaluation &amp; Iteration: design evals, measure performance rigorously, and improve systems using real-world feedback.
  </li>
  <li>
   AI-Assisted Development: use modern AI coding tools to move faster while maintaining high standards.
  </li>
  <li>
   Collaboration: work closely with product and engineering teams to deliver high-impact features.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What You&rsquo;ll Bring
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience: 2&ndash;5 years building and shipping ML or AI-powered systems into production.
  </li>
  <li>
   Strong Engineering Skills: clean, testable Python; solid software design; experience working in production environments.
  </li>
  <li>
   AI/ML Breadth: experience with either traditional ML (e.g. gradient boosting) and/or LLM systems (prompting, tool use, evals, agents).
  </li>
  <li>
   Systems Thinking: ability to reason about trade-offs (accuracy, latency, cost, reliability) and design accordingly.
  </li>
  <li>
   Data Skills: SQL, pandas, and experience working with messy real-world data.
  </li>
  <li>
   AI-Native Workflow: comfortable using AI-assisted coding tools effectively.
  </li>
  <li>
   Curiosity &amp; Ownership: proactive in exploring new approaches and improving existing systems.
  </li>
  <li>
   Collaboration: strong cross-functional working style.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We Offer In Return
  <br/>
  <br/>
 </strong>
 💰 Competitive salary of &pound;65,000 to &pound;75,000 depending on experience
 <br/>
 <br/>
 🏝️ 27 days of annual leave (including 3 days Christmas closing) which increases up to 3 days based on tenure, with the option to roll over, buy or sell up to 3 days
 <br/>
 <br/>
 🏡 Hybrid working with two days a week from our dog-friendly Hoxton office
 <br/>
 <br/>
 💪 On-site gym and cycle to work scheme
 <br/>
 <br/>
 🛍️ Employee discount at over 100 retailers
 <br/>
 <br/>
 🏥 Comprehensive private medical &amp; dental cover with Vitality
 <br/>
 <br/>
 🍼 Enhanced parental leave pay
 <br/>
 <br/>
 📚 Learning &amp; development culture &ndash; &pound;1,000 personal annual budget
 <br/>
 <br/>
 🌍 We&rsquo;re carbon-neutral and are working towards ambitious carbon reduction goals
 <br/>
 <br/>
 🎯 Lots of team socials &amp; activities
 <br/>
 <br/>
 ☀️ Annual team retreat
 <br/>
 <br/>
 <strong>
  Want to learn more?
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   About us
  </li>
  <li>
   Xelix blog
  </li>
  <li>
   Xelix news
  </li>
  <li>
   Xelix glassdoor
   <br/>
   <br/>
  </li>
 </ul>
 We believe that people from diverse backgrounds, with different identities and experiences make our company and product better. No matter your background, we'd love to hear from you! And if you have a disability, please let us know if there's any way we can make the interview process better for you - we're happy to accommodate!
 <br/>
 <br/>
 If you're a recruiting agency - we have an existing list of agencies we work with if required and we are not currently planning on expanding the list. Neither the Talent team nor hiring managers or the Support team will respond to cold outreach.
 <br/>
 <br/>
 This is a full-time position, with standard working hours from 9:00 AM to 6:00 PM, Monday through Friday.
 <br/>
 <br/>
 <strong>
  Interview Process
  <br/>
  <br/>
 </strong>
 While the exact process may vary slightly depending on the role, our typical interview stages are:
 <br/>
 <br/>
 <ul>
  <li>
   Introductory Call &ndash; A short Teams conversation with a Talent Partner to discuss your background and the opportunity.
  </li>
  <li>
   Hiring Manager Interview &ndash; A 30&ndash;45 minute Teams meeting to explore your experience and fit for the team.
  </li>
  <li>
   Technical Task or Presentation &ndash; A role-relevant exercise to demonstrate your skills and approach.
  </li>
  <li>
   Final On-site Interview &ndash; An in-person meeting with our senior leadership team and co-founders at our office.
   <br/>
   <br/>
  </li>
 </ul>
 We strive to make the process clear, efficient, and respectful of your time.
</div>


AI Engineer

JPMorganChase

<div><b>JOB DESCRIPTION</b><br>
<br>
<br>
<p>Become a member of a team where you can contribute significantly to shaping the future of a world-renowned and influential company. Among top performers, you can make a direct and meaningful impact.<br>
</p><p>As a Lead Engineer at JPMorgan Chase within our Market Data Services team you will play a pivotal role in designing, delivering and maintaining critical data distribution systems within the firm. These systems encompass both on-premises and cloud based infrastructure to deliver third party data to multiple lines of business.
<br>
You will be working within an Agile project environment collaborating closely with cross-functional teams to deliver high-quality solutions to our clients.</p><p><b>
Job Responsibilities</b></p><ul><li>
Applies deep technical expertise and problem-solving methodologies focused on analyzing complex data and systems, anticipating issues, considering upstream and downstream implications, and advising on mitigation actions</li><li>
Uses enterprise-authorized AI capabilities within the work environment to accelerate analysis of complex infrastructure signals and documentation of mitigation options, validating outputs and handling operational data according to sensitivity and security requirements.</li><li>
Designing and maintaining critical data delivery systems - encompassing both realtime data, historical data and AI/ML use-cases</li><li>
Collaboration with product owners and stakeholders to ensure data solutions align with business and regulatory requirements</li><li>
Capable of finding a balance between best of breed and cost effective solutions</li><li>
Act as a positive team player who is capable of accepting different intellectual points of view
</li><li>Clear and concise communicator; ability to present to senior management</li><li>
Ability to analyze and articulate problems and provide input into solutions</li><li>
Provide 3rd level support to operational roles
</li><li>A respect for strong process and control management disciplines</li><li>
Leads reuse-first adoption of AI-assisted practices across delivery and automation routines to reduce recurring issues, ensuring changes are validated, traceable and auditable, and aligned to resiliency and security expectations.</li></ul><p>
</p><p><b>Required qualifications, capabilities, and skills</b><br>
</p><ul><li>Formal training or certification on infrastructure engineering concepts and advanced applied experience in Cloud technologies including Kubernetes, Terraform and AWS
</li><li>Data Lake technologies (e.g. Snowflake, Databricks, AWS Glue/Athena, Lake Formation)</li><li>
Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity.</li><li>
Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations</li><li>
Network architecture and protocols
</li><li>Programming languages (e.g. Java, Python, C++)</li><li>
Market Data / messaging products (e.g. TREP, Vela, RedLine, Bloomberg BPIPE, Solace, AMPS, etc.)</li><li>
Market Data vendors and their key products (e.g. Bloomberg, LSEG, Factset, S&amp;P)</li><li>
Database technologies and SQL scripting</li><li>
Monitoring tools (ITRS Geneos, Dynatrace, Datadog)
<br>
</li></ul><b>ABOUT US</b>
<br>
<br>
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.<br>
<div><div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.<br>
</div></div><br>
<br>
<b>ABOUT THE TEAM</b>
<br>
<br>
J.P. Morgan's Commercial &amp; Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial &amp; Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.</div>

Senior Lead Infrastructure Engineer - Market Data - AWS / Snowflake

Bloomberg

<div>
 Location
 <br/>
 <br/>
 London
 <br/>
 <br/>
 Business Area
 <br/>
 <br/>
 Engineering and CTO
 <br/>
 <br/>
 Ref #
 <br/>
 <br/>
 10049302
 <br/>
 <br/>
 <strong>
  Description &amp; Requirements
  <br/>
  <br/>
 </strong>
 Bloomberg&rsquo;s Engineering AI department has 400+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products. At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.
 <br/>
 <br/>
 Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions.
 <br/>
 <br/>
 Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.
 <br/>
 <br/>
 We are looking for Senior ML Platform Engineers with strong expertise and passion for building platforms for (Gen) AI applications.
 <br/>
 <br/>
 As a Senior ML Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed AI development life cycle to enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as, Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud-native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source.
 <br/>
 <br/>
 <strong>
  Join the AI Group as a Senior ML Platform Engineer and you will have the opportunity to:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Architect, build, and diagnose multi-tenant AI platform systems
  </li>
  <li>
   Work closely with AI application teams to design seamless workflows for continuous model training, inference, and monitoring
  </li>
  <li>
   Work with AI experts to understand workflows, pinpoint, and resolve inefficiencies, and to inform the next set of features for the platforms
  </li>
  <li>
   Collaborate with open-source communities and AI application teams to build a cohesive MLOps experience
  </li>
  <li>
   Design CI/CD automation frameworks that incorporate regulatory requirements
  </li>
  <li>
   Develop cloud-native deployment patterns for AI systems across environments
  </li>
  <li>
   Troubleshoot and debug user issues
  </li>
  <li>
   Provide operational and user-facing documentation
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  We are looking for a Senior ML Platform Engineer with:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Proven years of experience working with an object-oriented programming language (Python, Go, etc.)
  </li>
  <li>
   Experience designing cloud-native, distributed platforms
  </li>
  <li>
   Strong knowledge of Kubernetes, Argo, and container orchestration technologies
  </li>
  <li>
   Previous experience with modern CI/CD tools and GitOps workflows
  </li>
  <li>
   Familiarity with implementing automation for model development lifecycles
  </li>
  <li>
   A proactive mentality and ability to collaborate with peers, stakeholders, and management
  </li>
  <li>
   A Degree in Computer Science, Engineering, Mathematics, or similar field of study or equivalent work experience
  </li>
  <li>
   An understanding of Computer Science fundamentals such as data structures and algorithms
   <br/>
   <br/>
  </li>
 </ul>
 We give back to the technology community and you can read more about our outreach at:
 <br/>
 <br/>
 If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
 <br/>
 <br/>
 Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.
</div>


Senior ML Platform Engineer - Artificial Intelligence

Ciklum

<p></p><div><div><div><div><div><div><div><div><div><div><div><b>Ciklum</b> is looking for a <b>Expert Agentic AI Engineer</b> to join our team full-time in the UK .<br>
We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live.</div><p><b>
About the role:</b></p><p>
As a Expert Agentic AI Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.</p><p><b>
Responsibilities:</b></p><ul><li>
Design, build, train, and deploy production-grade Machine Learning, Deep Learning, or Natural Language Processing (NLP) models</li><li>
Optimize ML models for enterprise-scale latency, throughput, and performance, ensuring flawless integration with data warehouses and automated workflow bots</li><li>
Partner with Data Engineers to engineer high-quality data pipelines, automated feature stores, and secure data preprocessing routines</li><li>
Establish and scale MLOps workflows to handle model lineage tracking, code versioning, automated validation gates, and continuous deployment pipelines</li><li>
Set the core technical direction for AI engineering across squads, evaluate emerging AI methodologies, and provide high-level mentorship to senior team members</li></ul><p><b>
Requirements:</b></p><ul><li>
5+ years (Senior) or 8+ years (Expert) of professional experience developing, shipping, and maintaining machine learning models in live production environments</li><li>
Agentic Frameworks: Hands-on experience building autonomous workflows, custom plugins, and orchestration logic using Microsoft Copilot Studio or semantic kernels</li><li>
Cloud AI Infrastructure: Proven experience deploying and fine-tuning generative AI models, prompt flow, and vector databases within Azure AI Foundry (formerly Azure AI Studio)</li><li>
Tool Integration: Strong background in connecting LLMs to external APIs, enterprise data sources, and robotic process automation (RPA) tools to enable autonomous action execution</li><li>
Elite proficiency in Python paired with extensive experience using core ML libraries and frameworks (such as PyTorch, TensorFlow, Scikit-Learn, or Hugging Face)</li><li>
Hands-on experience working with MLOps tracking tools and cloud-based AI infrastructure ecosystems (such as MLflow, Kubeflow, AWS SageMaker, or Azure ML)</li><li>
Strong computer science fundamentals, including advanced knowledge of data structures, algorithmic complexity, and clean code principles. a formal degree in Computer Science, Data Science, Mathematics, or a highly quantitative field is strongly preferred</li></ul><p><b>
What`s in it for you?</b></p><ul><li>
Strong community: Work alongside top professionals in a friendly, open-door environment</li><li>
Growth focus: Take on large-scale projects with a global impact and expand your expertise</li><li>
Tailored learning: Boost your skills with internal events (meetups, conferences, workshops), Udemy access, language courses, and company-paid certifications</li><li>
Endless opportunities: Explore diverse domains through internal mobility, finding the best fit to gain hands-on experience with cutting-edge technologies</li><li>
Care: Healthcare, Basic Life Insurance, Short and Long-term disability insurance according to the Company&rsquo;s Benefit Plans</li></ul><p><b>
About us:</b></p><p>
At Ciklum, we are always exploring innovations, empowering each other to achieve more, and engineering solutions that matter. With us, you&rsquo;ll work with cutting-edge technologies, contribute to impactful projects, and be part of a One Team culture that values collaboration and progress. In the UK, Ciklum is growing fast&mdash;inviting experienced professionals to lead digital transformation alongside Fortune 500 clients. Be part of a company where innovation and impact go hand in hand.</p><p><b>
Explore, empower, engineer with Ciklum!</b></p><p>
Interested already? We would love to get to know you! Submit your application. We can&rsquo;t wait to see you at Ciklum.</p><p>
#LI-VH1</p></div>
</div></div></div></div></div></div><div></div><div><div><div><div><div><div><p>REQUIRED SKILLS</p>
<div><ul><p>Agentic AI</p>
</ul></div></div></div></div></div></div></div><div></div><div><div><div><div><div><div><div>
</div></div></div></div></div></div></div><div><div><div><div><div><div><p>JOB INFO</p>
<div><div><div><ul><div><div>Job Identification</div>
<div>3619</div>
</div><div><div>Job Category</div>
<div>Intelligent Automation</div>
</div><div><div>Posting Date</div>
<div>07/03/2026, 02:34 AM</div>
</div><div><div>Locations</div>
<div> <div></div><div><div>London
</div></div>(Hybrid)</div></div></ul></div></div></div></div></div></div></div></div></div></div></div></div><p></p>

Expert Agentic AI Engineer

Autodesk

<div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p><b>Job Requisition ID #</b></p></div></div></div></div></div></div></div></div></div></div></div></div></div></div><div></div>
26WD99665<p></p><div><div><p><b>
Position Overview</b></p><p><b>
Senior QA Automation Engineer &ndash; AI Applications</b><b> UK</b></p></div><p></p><div><p><br>
We are seeking an experienced QA Automation Engineer to ensure the quality, reliability, and performance of AI-powered applications. The ideal candidate has expertise in automated testing and software quality engineering, with experience building scalable testing frameworks and leveraging AI-powered testing tools to improve test development, maintenance, and coverage. They combine deep QA automation expertise with practical experience using AI to enhance testing workflows. Experience testing AI/ML applications or validating machine learning models is an asset.</p></div><p></p><div><p><b><br>
Responsibilities</b></p></div><div><ul><li><p>
Design and maintain automated test suites, evaluation scenarios, metrics, and test datasets for AI-powered features</p></li></ul></div><div><ul><li><p>
Automate QA workflows using Python and CI/CD (e.g., GitHub Actions, Jenkins), leveraging AI-powered testing tools to improve test development, maintenance, and coverage</p></li></ul></div><div><ul><li><p>
Create and maintain test harnesses for AI services, applications, and APIs</p></li></ul></div><div><ul><li><p>
Perform API testing for AI services and backend systems</p></li></ul></div><div><ul><li><p>
Define quality strategy and acceptance criteria for AI-powered applications across functional, API, integration, and AI/ML features</p></li></ul></div><div><ul><li><p>
Test AI/ML applications and machine learning models from a product and user perspective</p></li></ul></div><div><ul><li><p>
Evaluate AI/ML model outputs for correctness, consistency, and expected application behavior</p></li></ul></div><div><ul><li><p>
Define structured rubrics that translate qualitative findings into measurable evaluation gates</p></li></ul></div><div><ul><li><p>
Build quality gates for CI/CD and deployment pipelines, including automated regression and integration testing</p></li></ul></div><div><ul><li><p>
Mentor teams on QA automation best practices and consistent quality standards for AI-powered applications</p></li></ul></div><div><ul><li><p>
Contribute to multi-team projects and codebases, ensuring code quality and consistency</p></li></ul></div><div><ul><li><p>
Participate in code reviews and provide constructive feedback to peers</p></li></ul></div><div><ul><li><p>
Document and present findings and ideas across the company</p></li></ul></div><p></p><div><p><b><br>
Minimum Qualifications</b></p></div></div><div><div><ul><li><p>
Bachelor&rsquo;s degree in Computer Science, Engineering, or equivalent experience</p></li></ul></div><div><ul><li><p>
5+ years of professional experience in software quality assurance, test automation, or software engineering</p></li></ul></div><div><ul><li><p>
Strong programming skills in Python, with experience in test automation</p></li></ul></div><div><ul><li><p>
Hands-on experience using AI-powered testing tools or AI coding assistants to improve test automation, productivity, and quality</p></li></ul></div><div><ul><li><p>
Experience with CI/CD tools and processes</p></li></ul></div><div><ul><li><p>
Familiarity with popular CAD environments and tooling</p></li></ul></div><div><ul><li><p>
Proficient in automation and UAT test suites/frameworks</p></li><li><p>
Experience designing QA frameworks or platforms used by multiple teams</p></li></ul></div><div><ul><li><p>
Excellent problem-solving skills and attention to detail</p></li></ul></div><div><ul><li><p>
Strong communication and collaboration skills</p></li></ul></div><div><ul><li><p>
Understanding of software architecture and design patterns</p></li></ul></div><div><ul><li><p>
Ability to work in an Agile development environment</p></li></ul></div><p></p><div><p><b>
Preferred Qualifications</b></p></div><div><ul><li><p>
Experience testing AI/ML applications or validating machine learning models</p></li></ul></div><div><ul><li><p>
Experience with data validation tooling (e.g., Great Expectations) or labeling workflows</p></li></ul></div><div><ul><li><p>
Familiarity with ML frameworks (e.g., PyTorch, TensorFlow)</p></li></ul></div><div><ul><li><p>
Experience with data pipelines and orchestration tools (e.g., Airflow, Metaflow)</p></li></ul></div><div><ul><li><p>
Knowledge of MLOps practices (e.g., model monitoring, drift detection, deployment validation)</p></li></ul></div><div><ul><li><p>
Knowledge of ML evaluation methods, metrics, and benchmarking</p></li></ul></div><div><ul><li><p>
Passion for learning new technologies and improving existing systems</p></li></ul></div></div><div><div><ul><li><p>
Experience with cloud providers (e.g., AWS, Azure, Google Cloud Platform)</p></li></ul></div><div><ul><li><p>
Experience testing AI/ML services in production environments</p></li></ul></div><div><ul><li><p>
Knowledge of experiment tracking tools (e.g., Comet, MLflow, Weights &amp; Biases)</p></li></ul></div><p></p><div><p><b>
The Ideal Candidate</b></p></div><div><ul><li><p>
You demonstrate initiative to provide solutions and to learn and develop new technologies</p></li></ul></div><div><ul><li><p>
Comfortable building QA systems from scratch and writing maintainable automation</p></li></ul></div><div><ul><li><p>
You enjoy learning and collaborating across global locations</p></li></ul></div><div><ul><li><p>
You are comfortable working in newly forming ambiguous areas</p></li></ul></div><div><ul><li><p>
You are comfortable building scalable and maintainable QA automation frameworks that will be relied on by others</p></li></ul></div><div><ul><li><p>
You effectively leverage AI-powered tools to improve testing workflows and engineering productivity</p></li></ul></div><div><ul><li><p>
You can communicate well with others</p></li></ul></div><p></p><div><p><br>
 #LI-JK3</p></div></div><p></p><p><b><br>
Learn More</b></p><p></p><p><b>
About Autodesk</b></p><p>
Welcome to Autodesk! Amazing things are created every day with our software &ndash; from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.</p><p></p><p>
We take great pride in our culture here at Autodesk &ndash; it&rsquo;s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.</p><p></p><p>
When you&rsquo;re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!</p><p></p><p><b>
Salary transparency</b></p>
Salary is one part of Autodesk&rsquo;s competitive compensation package. Offers are based on the candidate&rsquo;s experience and geographic location. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.<p><b><br>
Belonging</b><br>
We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging</p><p></p><p><b>
Are you an existing contractor or consultant with Autodesk?
</b></p><p>Please search for open jobs and apply internally (not on this external site).</p></div>

Senior QA Automation Engineer – AI Applications UK

Google

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience.<br>
</li>
<li>5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.</li>
<li>5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.<br>
</li>
<li>5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Master&rsquo;s degree or PhD in Engineering, Computer Science, or a related technical field.<br>
</li>
<li>5 years of experience with data structures and algorithms.</li>
<li>3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.</p>
<p>
In this role, you will be at the forefront of applying Google's Generative AI to solve real-world issues for our customers. You will act as a specialized software engineer embedded with key accounts, working to build, deploy, and optimize sophisticated AI agents on our Customer Engagement Suite (CES) platform. You will bridge the gap between our core product developing teams and customer needs, directly accelerating customer success and shaping the future of our AI products.</p><p>
The Cloud Applied AI (AAI) powers business growth with Gemini Enterprise. Our portfolio includes Gemini Enterprise for Customer Experience (Shopping Agent, CX Agent Studio, Agent Assist, Vertex AI Search - Commerce, Customer Experience Insights), along with other vertical and domain packaged solutions. We enable high adoption and speed to value by building solutions that are quickly deployed, delivering new 0-to-1 capabilities with startup agility. Team members operate at the forefront of AI, collaborating directly with model builders with unprecedented speed. Join us to work on cutting-edge projects and shape the future of AI in a fast-paced, collaborative, and impactful environment.</p></div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Partner directly with customers to understand their business issues. Design, co-develop, debug, and deploy custom conversational AI agents and solutions to accelerate their time to value.</li>
<li>Systematize learnings from customer engagements by creating reusable tools, building documentation and accelerators, and establishing best practices across the organization.</li>
<li>Act as a high-level problem solver, empowered to write bespoke code, develop custom tooling, and even contribute directly to the core product codebase to resolve critical customer issues.<br>
</li>
<li>Lead the design and implementation of solutions in specialized ML areas, optimize ML infrastructure, and guide the development of model optimization and data processing strategies.<br>
</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>

Software Engineer, Applied AI, Agent Building, Google Cloud Platform

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