software engineer

data engineer

ai engineer

machine learning engineer

senior software engineer

software engineer   ai ml

Google

<div>
 <strong>
  Minimum qualifications:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Currently enrolled in or graduated from a PhD program.
  </li>
  <li>
   Research experience in Artificial Intelligence, Distributed Systems, Machine Learning, Data Mining, Natural Language Processing, Image Classification, Spam Fighting, or related fields.
  </li>
  <li>
   Experience in computer science and software design.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred qualifications:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience working with Generative AI.
  </li>
  <li>
   Experience with data structures and algorithms.
  </li>
  <li>
   Knowledge of Python programming.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About The Job
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 AI in the Gemini Era is data-centric: the quality of the data used for training, fine-tuning, or RAG, matters more to the performance of the end product than almost anything else.
 <br/>
 <br/>
 Our mission is to improve the quality of models that Google releases through its various product offerings by providing tools and services for making faster and easier to reach model quality goals. We do so by bringing data optimization techniques to a broad audience through integrated tools and platforms. We build and iterate tools to automatically and efficiently apply data optimization techniques. We demonstrate to our users which ones work best for their use case, and deliver insights on how to improve further. We&rsquo;re working with key product teams across Google.
 <br/>
 <br/>
 Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Help scaling data optimization techniques improving the performance and quality of ML models.
  </li>
  <li>
   Work closely with our Research teams as well as ML practitioners to identify, build and iterate on engineering tools, processing pipelines, data optimization techniques.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 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, AI/ML, PhD, Early Career

JPMorganChase

<div><b>JOB DESCRIPTION</b><br>
<br>
<br>
<p>Help shape how intelligent systems are built and delivered at JPMorganChase. In this role, you'll contribute to the LLM Suite platform by building AI/ML and agentic capabilities that are secure, reliable, and ready for production. You'll collaborate closely with senior engineers, learn through real design discussions, and grow your technical depth across cloud and modern AI frameworks. If you enjoy solving tough problems and iterating quickly with feedback, you'll fit right in.<br>
</p><p><br>
As an Applied AI ML Engineer in LLM Suite Engineering, Senior Associate, you will design, build, and troubleshoot software that enables AI/ML and agentic experiences on the platform. You will write secure, high-quality code and support algorithms that integrate with existing systems. You will collaborate with senior engineers on designs and implementation choices, focusing on reliability and operational stability. You will help deliver GenAI services using public cloud capabilities. You will explore and operationalize emerging patterns such as agent-to-agent communication, model context protocols, and agentic orchestration, turning early-stage concepts into scalable, production-ready capabilities. You will contribute as a team player who seeks and applies feedback.</p><p>
</p><p><b>Job Responsibilities</b></p><ul><li>
Design, develop, and troubleshoot software solutions using creative approaches to solve complex technical challenges</li><li>
Write secure, high-quality production code and maintain algorithms that integrate with existing systems</li><li>
Collaborate with senior engineers and participate in design discussions</li><li>
Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks</li><li>
Implement GenAI services leveraging Azure OpenAI models and AWS Bedrock</li><li>
Collaborate openly with the team, seek feedback, and apply it to improve outcomes</li></ul><p>
</p><p><b>Required Qualifications, Capabilities, and Skills</b></p><ul><li>
Computer science degree or equivalent practical experience</li><li>
Hands-on experience with system design, application development, testing, and operational stability</li><li>
Strong understanding of the Software Development Life Cycle</li></ul><p>
</p><p><b>Preferred Qualifications, Capabilities, and Skills</b></p><ul><li>
Experience implementing GenAI services leveraging Azure OpenAI models and AWS Bedrock</li><li>
Proficiency in Python (FastAPI)</li><li>
Experience building microservices and APIs</li><li>
Experience with elastic compute, NoSQL databases, and messaging queues</li><li>
Proficiency working with large language models and building agents with LangGraph</li><li>
Experience developing, debugging, and maintaining code in a large corporate environment using modern programming and database querying languages, including containerization</li>
Knowledge of agent-to-agent (A2A) communication, Model Context Protocol (MCP), AI skills development, personal AI assistants, or agentic orchestrators<br>
<li>
<br>
#LLMSuiteEngineering_jobs</li></ul>
<b>ABOUT US</b><br>
<br>
<br>
<div><p>JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.<br>
<br>
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.</p><br>
</div><br>
<br>
<b>ABOUT THE TEAM</b>
<br>
<br>
Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.</div>

Applied AI ML Software Engineer III - LLM Suite Engineering - Senior Associate

Universal Music Group UK

<div>
 Music is Universal
 <br/>
 <br/>
 It&rsquo;s the passionate and dedicated team at Universal Music who help make us the world&rsquo;s leading music company. From A&amp;R to finance, legal to digital, sales to marketing, Universal Music is the place to grow and develop your career within a truly commercial and innovative business that leads in everything it does.
 <br/>
 <br/>
 Everyone is welcome to apply for our roles, and we are determined to ensure that no applicant or employee receives less favourable treatment because of gender, race, disability, sexual orientation, religion, belief, age, marital status, background, pregnancy, or caring responsibilities. We also recognise the importance of diversity of thought within our teams and are fully committed to embracing the talents of people with autism, dyslexia, ADHD, and other forms of neurocognitive variation.
 <br/>
 <br/>
 We will always seek to make appropriate adjustments to recruitment, workplaces, and work processes to be fully inclusive to people with different needs and working styles. If you need us to make any reasonable adjustments for you from application onwards, including alternatives to the online form or to disclose a neurocognitive condition, please email UniversalMusicCareers@umusic.com.
 <br/>
 <br/>
 <strong>
  Department
  <br/>
  <br/>
 </strong>
 Part of the Global Technology organization, the team&rsquo;s mission is to design and build state of the art AI/ML tools to support and empower Royalty Manager &amp; Artists, and industry professionals.
 <br/>
 <br/>
 The team covers the full design &amp; development lifecycle, from explorative research to design to prototypes to production scale programs. It typically undertakes programs with applications such as, but not limited to, royalty calculations, income claim, contract agreements, search, recommendation, etc.
 <br/>
 <br/>
 We are curious, passionate and committed to push the envelope in AI for music. If you are excited at the idea of working on state-of-the-art AI at industry scale and make an impact, we want to hear from you!
 <br/>
 <br/>
 <strong>
  The Role
  <br/>
  <br/>
 </strong>
 We&rsquo;re looking for an AI Developer to build and ship machine learning and generative AI solutions that power how a modern music company operates across A&amp;R insights, marketing optimization, audience growth, content operations, rights/royalty workflows, and creative tools. You&rsquo;ll partner with product, engineering, data, legal, and business teams to take ideas from prototype to production, with a strong focus on reliability, safety, and measurable impact.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <strong>
  Be Technical
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and implement AI pipelines for automating royalty calculation and relation processes etc.
  </li>
  <li>
   Integrate foundation models (LLMs, vision models, etc.) into products using APIs and custom fine-tuning.
  </li>
  <li>
   Develop and maintain retrieval systems that operate efficiently at scale.
  </li>
  <li>
   Explore frontier software engineering in AI/ML for media, and related opportunities for UMG.
  </li>
  <li>
   Build on state-of-the-art cloud infrastructure.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Be collaborative
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Collaborate with the team and stakeholders to deliver, operate and maintain products.
  </li>
  <li>
   Be part of an innovative and dynamic team.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Skills And Experience Required
  <br/>
  <br/>
 </strong>
 <strong>
  Must have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Background in Computer Science, Software Engineering, ML Ops, Artificial Intelligence or related technical field.
  </li>
  <li>
   5+ years of hands-on professional experience in software/ML engineering.
  </li>
  <li>
   Proven ability to come up with designs for AI/ML systems, pipelines and/or applications, and to implement them successfully.
  </li>
  <li>
   Expertise in quantitative evaluation and benchmarking of state-of-the-art AI models.
  </li>
  <li>
   Up to date knowledge of state of the art for ML Ops, ML infrastructure, including related tools, design patterns, best practices etc.
  </li>
  <li>
   Experience with vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate) and information retrieval systems and methods.
  </li>
  <li>
   Familiarity with media content (video, audio) ML pipelines.
  </li>
  <li>
   Proficiency in Python and common AI/ML libraries (e.g., PyTorch, Hugging Face Transformers, LangChain) and cloud frameworks (VertexAI, Bedrock, Sagemaker).
  </li>
  <li>
   Strong proficiency in Git, CI/CD workflows, and containerization (Docker/Kubernetes).
  </li>
  <li>
   Proficiency with Linux environments and cloud platforms (e.g. AWS, Google Cloud Platform).
  </li>
  <li>
   Ability to write clean, efficient, well documented, and reusable code.
  </li>
  <li>
   Good communication skills, both oral and written.
  </li>
  <li>
   Curious, self-motivated, and proactive.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice to have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience training and/or fine-tuning AI models.
  </li>
  <li>
   Experience with LLMs integration, fine-tuning and associated tools (e.g. LangChain, Agent frameworks).
  </li>
  <li>
   Competency in at least one other programming language (e.g. C/C++, Java).
  </li>
  <li>
   Experience going from POC to production-grade system.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Key Behaviours
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Curious Innovator: You stay up to date with frontier AI technologies and enjoy experimenting with fresh ideas that push the boundaries, running experiments, and learning fast from results.
  </li>
  <li>
   Ownership Mindset: You take initiative, follow through on challenges, and bring a sense of accountability to everything you build.
  </li>
  <li>
   Pragmatic Problem Solver: You balance technical depth with real-world practicality &mdash; delivering elegant, efficient and robust solutions that get the job done.
  </li>
  <li>
   Collaborative Builder: You thrive in cross-functional teams, translating complex AI concepts into simple, impactful solutions that empower others.
  </li>
  <li>
   Culturally Connected: You have a genuine interest in music and the role of technology in supporting culture.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About UMG UK
  <br/>
  <br/>
 </strong>
 We are Universal Music Group UK &ndash; the UK&rsquo;s leading music-based entertainment company. We exist to shape culture through the power of artistry. We help UK artists produce, distribute and promote the most critically acclaimed and commercially successful music to inspire and entertain fans at home and around the world.
 <br/>
 <br/>
 <strong>
  Bonus Tracks: Your Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Group Personal Pension Scheme (between 3% and 9%)
  </li>
  <li>
   Private Medical Insurance
  </li>
  <li>
   25 paid days of annual leave
  </li>
  <li>
   Interest Free Season Ticket Loan
  </li>
  <li>
   Holiday Purchase scheme
  </li>
  <li>
   Dental and Travel Insurance options
  </li>
  <li>
   Cycle to Work Scheme
  </li>
  <li>
   Salary Sacrifice Cars
  </li>
  <li>
   Subsidised Gym Membership
  </li>
  <li>
   Employee Discounts (Reward Gateway)
   <br/>
   <br/>
  </li>
 </ul>
 Just So You Know&hellip;
 <br/>
 <br/>
 The company presents this job description as a guide to the major areas and duties for which the jobholder is accountable. However, the business operates in an environment that demands change and the jobholder's specific responsibilities and activities will vary and develop. Therefore, the job description should be seen as indicative and not as a permanent, definitive, and exhaustive statement.
 <br/>
 <br/>
 <strong>
  Job Category
  <br/>
  <br/>
 </strong>
 Universal Music Group
</div>


AI Developer

Ultralytics

<div>
 <strong>
  About Ultralytics:
  <br/>
  <br/>
 </strong>
 At Ultralytics, we commit to relentless innovation in the AI space and seek team members who resonate with our ambition to produce the world's best YOLO AI models. If you're obsessed with AI, eager to make an impact on the world and thrive in dynamic, high-intensity environments, we invite you to apply for a position on our team.
 <br/>
 <br/>
 <strong>
  🌎 Location and Legalities
  <br/>
  <br/>
 </strong>
 This full-time LLM Engineer position is based onsite in our brand-new Ultralytics office in London, UK. Applicants must have legal authorization to work in the UK, as Ultralytics does not provide visa sponsorship.
 <br/>
 <br/>
 <strong>
  🚀 What You'll Do
  <br/>
  <br/>
 </strong>
 As an LLM Engineer at Ultralytics, you will spearhead the development and integration of advanced language model capabilities across our ecosystem. You will work on cutting-edge projects that merge the power of Large Language Models (LLMs) with our state-of-the-art computer vision technologies. Key responsibilities include:
 <br/>
 <br/>
 <ul>
  <li>
   Developing and scaling robust LLM-powered applications using a variety of APIs, including OpenAI, Anthropic, and Gemini.
  </li>
  <li>
   Implementing and managing multi-API workflows using tools like LiteLLM to ensure flexibility and resilience.
  </li>
  <li>
   Building sophisticated Retrieval-Augmented Generation (RAG) systems, leveraging advanced techniques like embeddings with Voyage AI, rerankers, and query enrichment.
  </li>
  <li>
   Designing and maintaining efficient data pipelines and vector storage solutions using MongoDB Atlas Vector Search.
  </li>
  <li>
   Fine-tuning LLMs on custom datasets to enhance performance for specialized tasks related to our documentation and user support.
  </li>
  <li>
   Collaborating with our YOLO development team to explore and build innovative multi-modal solutions.
  </li>
  <li>
   Automating deployment and testing processes using CI/CD pipelines with GitHub Actions.
   <br/>
   <br/>
  </li>
 </ul>
 Your work will directly enhance the Ultralytics HUB platform and empower our global community of developers and researchers.
 <br/>
 <br/>
 <strong>
  🛠️ Skills And Experience
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   5+ years of experience in software engineering, with a strong focus on AI and Machine Learning (ML).
  </li>
  <li>
   Expert-level proficiency in Python and deep learning frameworks, particularly PyTorch.
  </li>
  <li>
   Proven experience building and deploying applications with LLM APIs such as OpenAI, Anthropic, Gemini, and DeepSeek.
  </li>
  <li>
   Hands-on experience with the full RAG pipeline, including vector embeddings, rerankers, and data indexing in databases like MongoDB.
  </li>
  <li>
   Practical knowledge of LLM fine-tuning, prompt engineering, and performance optimization.
  </li>
  <li>
   Familiarity with MLOps principles and tools, including CI/CD with GitHub Actions.
  </li>
  <li>
   A strong interest in computer vision and an understanding of object detection models like Ultralytics YOLO11 is a significant plus.
  </li>
  <li>
   Excellent problem-solving skills and the ability to perform in a fast-paced, high-intensity environment.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  🌟 Cultural Fit - Intensity Required
  <br/>
  <br/>
 </strong>
 Ultralytics is a high-performance environment for world-class talent obsessed with achieving extraordinary results. We operate at a relentless pace, demanding exceptional dedication and an unwavering commitment to excellence, guided by our mission, vision, and values. Our team thrives on audacious goals and absolute ownership. This is not a conventional workplace. If your priority is predictable comfort or a standard work-life balance over the relentless pursuit of progress, Ultralytics is not for you. We seek driven individuals prepared for the profound personal investment required to make a defining contribution to the future of AI.
 <br/>
 <br/>
 <strong>
  💶 Compensation And Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive Salary: Highly competitive based on experience.
  </li>
  <li>
   Startup Equity: Participate directly in our company's growth and success.
  </li>
  <li>
   Hybrid Flexibility: 3 days per week in our brand-new office - 2 days remote.
  </li>
  <li>
   Generous Time Off: 24 days vacation, your birthday off, plus local holidays.
  </li>
  <li>
   Flexible Hours: Tailor your working hours to suit your productivity.
  </li>
  <li>
   Tech: Engage with cutting-edge AI projects and contribute to leading open-source software.
  </li>
  <li>
   Gear: Brand-new Apple MacBook and Apple Display provided.
  </li>
  <li>
   Team: Become part of a supportive and passionate team environment.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What we offer:
  <br/>
  <br/>
 </strong>
 <strong>
  Cutting-Edge-next generation AI computer vision technology:
 </strong>
 contribute to building cutting edge computer vision AI models based on the YOLO framework.
 <br/>
 <br/>
 <strong>
  Impactful Work:
 </strong>
 Shape the future of AI-powered solutions that transform industries.
 <br/>
 <br/>
 <strong>
  Collaborative Culture:
 </strong>
 Join a talented and passionate team that values open communication and innovation.
 <br/>
 <br/>
 <strong>
  Ultralytics Handbook
  <br/>
  <br/>
 </strong>
 Comprehensive guide to our company&rsquo;s mission, vision, values, and operational practices. This handbook is designed to provide key insights and resources for our (future) team members, collaborators, and community to align with Ultralytics' core principles.
 <br/>
 <br/>
 Link: https://handbook.ultralytics.com/
 <br/>
 <br/>
 <em>
  Ultralytics is an equal opportunity employer and are committed to building an inclusive workplace. We believe that everyone should be able to bring their whole selves to work, and we do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status.
  <br/>
  <br/>
 </em>
</div>


LLM 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

<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

Hiscox

<div>
 <strong>
  Job Type
  <br/>
  <br/>
 </strong>
 Permanent
 <br/>
 <br/>
 <strong>
  Build a brilliant future with Hiscox
  <br/>
  <br/>
 </strong>
 <strong>
  Principal Machine Learning Engineer
  <br/>
  <br/>
 </strong>
 <strong>
  Location:
 </strong>
 London/York
 <br/>
 <br/>
 <strong>
  Why Hiscox London Market
  <br/>
  <br/>
 </strong>
 Hiscox London Market sits at the centre of global specialist insurance, tackling some of the most complex and unusual risks in the world. These are not commoditised problems, they demand deep expertise, strong judgement, and increasingly, sophisticated data and machine learning capabilities.
 <br/>
 <br/>
 We have a strong track record of putting AI into real production use, from augmenting underwriting decisions to shaping future market standards through partnerships and market‑first innovation. This is an environment where advanced ML systems are expected to operate reliably, safely, and at scale, not remain in experimentation.
 <br/>
 <br/>
 You&rsquo;ll join a culture that values technical excellence, ownership, and courage, where senior individual contributors are trusted to set direction, challenge thinking, and build platforms that matter. For a Principal Machine Learning Engineer, this is a chance to work on high‑impact ML systems, influence how AI is adopted across the London Market, and help shape the future of insurance.
 <br/>
 <br/>
 <strong>
  Role Purpose
  <br/>
  <br/>
 </strong>
 As a
 <strong>
  Principal Machine Learning Engineer (MLE)
 </strong>
 , you bring a wealth of experience in building, scaling, and operating production machine learning systems, and use that experience to provide deep technical leadership across machine learning engineering and MLOps.
 <br/>
 <br/>
 You play a key role in shaping the architectural strategy for production ML systems and the ML Platform, working closely with Data Science, Engineering, and Platform teams to define patterns, standards, and tooling that enable reliable, repeatable delivery at scale. Through hands‑on contribution, design leadership, and technical mentorship, you help teams navigate complex technical decisions and build robust, maintainable systems.
 <br/>
 <br/>
 A central focus of the role is enabling the organisation to move quickly without sacrificing quality, evolving the ML platform, supporting the transition from experimentation to production, and helping teams adopt modern engineering practices. This includes championing the effective and responsible use of AI‑assisted development tools as part of a broader approach to improving developer experience, system quality, and long‑term sustainability.
 <br/>
 <br/>
 Success in this role comes from the practical application of deep experience, strong architectural thinking, and the ability to help others build better systems that deliver real business value.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <strong>
  Technical Leadership &amp; Ownership (Individual Contributor)
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Act as the technical lead for Machine Learning Engineering and MLOps across London Market.
  </li>
  <li>
   Technically lead the most complex and business‑critical ML systems, from architectural design through to production operation.
  </li>
  <li>
   Define and evolve production ML patterns and best practices, covering deployment, orchestration, monitoring, retraining, and decommissioning.
  </li>
  <li>
   Lead deep technical decision‑making, balancing scalability, reliability, security, and developer experience.
  </li>
  <li>
   Contribute hands‑on to critical systems, frameworks, and platform components where the complexity or impact demands it.
  </li>
  <li>
   Define best practices and guardrails for the use of AI‑assisted coding tools, ensuring they are used to improve productivity and code quality without compromising maintainability or operational safety.
  </li>
  <li>
   Lead by example in applying AI‑assisted development techniques (e.g. for prototyping, refactoring, and accelerating complex engineering work) with strong engineering judgement.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  ML Platform Strategy &amp; Build‑Out
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Partner closely with Group and Platform teams to design, build, and evolve the ML Platform, ensuring it supports:
  </li>
  <ul>
   <li>
    Reusable and scalable deployment patterns
   </li>
   <li>
    CI/CD for machine learning
   </li>
   <li>
    Full model lifecycle management
   </li>
   <li>
    Monitoring, observability, and alerting
   </li>
   <li>
    Secure and compliant operation
   </li>
  </ul>
  <li>
   Shape platform standards and interfaces that enable consistent ML delivery across squads and value streams.
  </li>
  <li>
   Lead technical spikes and proof‑of‑concepts to evaluate new tools, approaches, and architectural patterns.
  </li>
  <li>
   Influence developer tooling choices so that AI‑assisted coding tools integrate safely with CI/CD, testing, and governance workflows.
  </li>
  <li>
   Ensure the platform enables fast, safe experimentation while supporting robust, long‑lived production systems.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Governance, Reliability &amp; Commercial Impact
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Ensure ML systems meet architecture, security, compliance, and operational standards.
  </li>
  <li>
   Define and implement robust frameworks for monitoring technical health, model performance, and commercial impact of ML systems in production.
  </li>
  <li>
   Champion operational excellence across ML services, including monitoring, alerting, incident management, and post‑incident learning.
  </li>
  <li>
   Ensure clear ownership and lifecycle management for models and ML‑backed services.
  </li>
  <li>
   Promote responsible use of automation and AI‑assisted tooling in safety‑critical or regulated contexts.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Collaboration &amp; Influence
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Work closely with the Data Science team to ensure a smooth and repeatable transition from experimentation to production.
  </li>
  <li>
   Collaborate with software engineers, product managers, and business stakeholders to deliver end‑to‑end ML‑driven solutions.
  </li>
  <li>
   Act as a senior technical voice in design reviews, architecture forums, and strategic discussions.
  </li>
  <li>
   Influence technical direction and standards through expertise, credibility, and collaboration rather than line management.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Technical Mentorship &amp; Capability Development
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Provide hands‑on technical mentorship to Machine Learning Engineers and Data Scientists.
  </li>
  <li>
   Raise engineering standards by sharing best practices, patterns, and lessons learned from real production systems.
  </li>
  <li>
   Coach teams on the effective and critical use of AI‑assisted coding tools, reinforcing the importance of code review discipline, testing, and long‑term maintainability.
  </li>
  <li>
   Contribute to technical hiring, assessment, and onboarding from a senior engineering perspective.
  </li>
  <li>
   Help shape long‑term capability by identifying gaps in tooling, skills, and platform maturity.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What You&rsquo;ll Bring
  <br/>
  <br/>
 </strong>
 <strong>
  Experience &amp; Background
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or a related quantitative field (or equivalent experience).
  </li>
  <li>
   Extensive experience as a senior or principal Machine Learning Engineer delivering production ML systems at scale.
  </li>
  <li>
   Proven track record of owning or shaping ML platforms, MLOps frameworks, or critical ML infrastructure.
  </li>
  <li>
   Experience operating in complex, cross‑functional environments (insurance or financial services experience is advantageous but not essential).
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Technical Expertise
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Exceptional Python skills in a machine learning engineering context, with strong software engineering fundamentals (OOP, testing, design patterns).
  </li>
  <li>
   Deep experience building, deploying, and operating production ML systems, including:
  </li>
  <ul>
   <li>
    Online and batch model serving
   </li>
   <li>
    Monitoring, alerting, and observability
   </li>
   <li>
    Retraining and lifecycle management
   </li>
  </ul>
  <li>
   Strong understanding of core data science concepts, sufficient to:
  </li>
  <ul>
   <li>
    Review and challenge modelling approaches
   </li>
   <li>
    Ensure models are production‑ready and correctly evaluated
   </li>
  </ul>
  <li>
   Hands‑on experience with a major cloud platform (AWS, GCP, or Azure), including containerised deployments.
  </li>
  <li>
   Expert knowledge of MLOps and CI/CD, including:
  </li>
  <ul>
   <li>
    Git‑based workflows
   </li>
   <li>
    Infrastructure as Code (e.g. Terraform)
   </li>
   <li>
    Automated testing and deployment pipelines
   </li>
  </ul>
  <li>
   Strong operational mindset, including APIs, logging, monitoring, reliability, and incident response.
  </li>
  <li>
   Working knowledge of SQL and integration of ML services into wider data and application ecosystems.
  </li>
  <li>
   Experience using AI‑assisted coding tools in a production engineering context, with a clear understanding of their benefits, limitations, and risks.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Why Join Us?
  <br/>
  <br/>
 </strong>
 This is an opportunity to shape the future of machine learning engineering at Hiscox, build a high-performing sub-chapter, and influence strategic decisions, while staying close to the craft you love. You&rsquo;ll have the autonomy to set standards, mentor talent, and explore emerging technologies, all within a collaborative and forward-thinking environment.
 <br/>
 <br/>
 <em>
  Work with amazing people and be part of a unique culture
 </em>
</div>


Principal Machine Learning Engineer

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