data engineer

software engineer

ai engineer

machine learning engineer

senior software engineer

software engineer   machine learning

Prima

<div>
 Are you looking for a new challenge?
 <br/>
 <br/>
 Fancy helping us shape the future of motor insurance?
 <br/>
 <br/>
 Prima could be the place for you.
 <br/>
 <br/>
 Since 2015, we&rsquo;ve been using our love of data and tech to rethink motor insurance and bring drivers a great experience at a great price. Our story began in Italy, where we&rsquo;ve quickly become the number one online motor insurance provider. In fact, we&rsquo;re trusted by over 5 million drivers. And now we&rsquo;re expanding to help millions more drivers in the UK and Spain.
 <br/>
 <br/>
 To help fuel that growth, we need a
 <strong>
  Senior Machine Learning Engineering
 </strong>
 to join our
 <strong>
  Engineering
 </strong>
 <strong>
  Team
 </strong>
 .
 <br/>
 <br/>
 This team is the beating heart of Prima.
 <br/>
 <br/>
 You&rsquo;ll be joining over 350 engineers across software development, infrastructure, operations and security. Fueled by curiosity, experimentation and collaboration, you&rsquo;ll help deliver scalable, impactful solutions that shape the future of insurance.
 <br/>
 <br/>
 <strong>
  Excited to make an impact? Here are the details
  <br/>
  <br/>
 </strong>
 <strong>
  What You Will Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Defining the model development methodologies and best practices, following the whole life cycle with a central role in choosing the technological stack;
  </li>
  <li>
   Supporting the productionalization and evolution of the Oracles, entities that through machine learning pilot the behavior of Prima's microservices;
  </li>
  <li>
   Developing the tools (packages, microservices, pipelines...) that you deem fundamental for your and your team job;
  </li>
  <li>
   Growing, reading, and experimenting to always be up to speed with emerging technology.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We&rsquo;re Looking For
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   A robust programming background, spotlighting your prowess in Python;
  </li>
  <li>
   A familiarity with the lifecycle of ML model development, including past experience in taking them to production;
  </li>
  <li>
   Proficiency in software development practices like TDD and BDD, ensuring our code is marked by quality, readability, and maintainability;
  </li>
  <li>
   A wealth of experience in software architecture, encompassing an understanding of common design patterns. Your focus on Machine Learning, Microservices, and DDD sets you apart;Exceptional command of the English language.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice-to-Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Alongside the essential prerequisites, we're excited to find experience in version control of data and artefacts (like DeltaLake, DVC, or MLFlow), designing and operating cloud-based systems, preferably within AWS or Databricks, familiarity with messaging platforms and proficiency in infrastructure as code (e.g. Terraform, CloudFormation, Pulumi), a grasp of K8s and service mesh concepts, and previous exposure to data orchestration tools.
   <br/>
   <br/>
  </li>
 </ul>
 &pound;70,000 - &pound;105,000 a year
 <br/>
 <br/>
 <strong>
  Why You&rsquo;ll Love It Here
  <br/>
  <br/>
 </strong>
 We want to make Prima a happy and empowering place to work. So if you decide to join us, you can expect plenty of perks.
 <br/>
 <br/>
 <strong>
  🤸 Work Your Way:
 </strong>
 Enjoy full flexibility &ndash; work from home, the office or a mix of both. Plus, work from anywhere for up to 30 days a year.
 <br/>
 <br/>
 <strong>
  🏁 Grow with us:
 </strong>
 We may move fast at Prima, but we move together. Get access to learning resources, mentorship and a growth plan tailored to you.
 <br/>
 <br/>
 <strong>
  🌈 Thrive and perform:
 </strong>
 Your best work begins when you feel your best. Enjoy private healthcare, gym discounts, wellbeing programs and mental health support.
 <br/>
 <br/>
 Think you&rsquo;re a match? Apply now.
 <br/>
 <br/>
 At Prima, we celebrate uniqueness. If you don&rsquo;t meet every requirement but are passionate about this role, we still want to hear from you. Innovation thrives on diverse perspectives.
 <br/>
 <br/>
 <em>
  Prima is proud to be an equal opportunity employer. Need accommodations during the process? Email us at accessible.recruiting@prima.it. Let&rsquo;s build the future of insurance, together.
 </em>
</div>


Senior Machine Learning Engineer

Helsing

<div>
 <strong>
  Who We Are
  <br/>
  <br/>
 </strong>
 Helsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve technological leadership, so that open societies can continue to make sovereign decisions and control their ethical standards.
 <br/>
 <br/>
 As democracies, we believe we have a special responsibility to be thoughtful about the development and deployment of powerful technologies like AI. We take this responsibility seriously.
 <br/>
 <br/>
 We are an ambitious and committed team of engineers, AI specialists and customer-facing programme managers. We are looking for mission-driven people to join our European teams &ndash; and apply their skills to solve the most complex and impactful problems. We embrace an open and transparent culture that welcomes healthy debates on the use of technology in defence, its benefits, and its ethical implications.
 <br/>
 <br/>
 <strong>
  The role
  <br/>
  <br/>
 </strong>
 At Helsing, we are pioneering the future of autonomous decision-making for defence. Our work spans the full AI landscape, including high-volume data processing, RL agent training, and large-scale foundation models. As a member of a cross-functional team, you will architect and implement the tools and platforms that enable these breakthroughs. Your focus will be on abstracting complex distributed systems to maximise training throughput and developer velocity. We are looking for engineers who can navigate the convergence of machine learning and systems engineering to build robust, scalable platforms.
 <br/>
 <br/>
 <strong>
  What you will do:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Extend our highly integrated deep learning frameworks (built on top of PyTorch), making them efficient and easy to use for a wide range of use cases.
  </li>
  <li>
   Scale our current infrastructure and tooling stack to support faster and larger distributed training.
  </li>
  <li>
   Design data strategy to support large scale datasets and efficient storage, ensuring GPUs stay warm.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  You should apply if you:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Hold an MSc or PhD in Computer Science or STEM field, with a focus on Machine Learning and Deep Learning.
  </li>
  <li>
   Have strong software engineering skills in Python and fluency with modern DL frameworks (PyTorch/JAX/TensorFlow). You don&rsquo;t just import libraries; you are comfortable writing custom layers, loss functions, and distributed training loops.
  </li>
  <li>
   Are a clear communicator who can build from complex theoretical concepts and contribute to the company's internal engineering culture.
  </li>
  <li>
   Have a "first-principles" mindset: you enjoy reading the latest AI optimisation blog posts and integrating them into codebases rapidly.
  </li>
  <li>
   You have debugged production ML pipelines and can tell a good war story about finding a subtle numerical or performance issue.
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  Note: We operate at an intersection where women, as well as other minority groups, are systematically
 </em>
 <em>
  under-represented. We encourage you to apply even if you don&rsquo;t meet all the listed qualifications; ability and impact cannot be summarised in a few bullet points.
  <br/>
  <br/>
 </em>
 <strong>
  Nice to have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   You have hands-on experience training models on large-scale GPU clusters, implementing advanced parallelism strategies, and understanding the underlying cross-node communication patterns (NCCL, MPI).
  </li>
  <li>
   You have worked with large-scale datasets made of different modalities. Understanding the tradeoffs in locality, encoding, formats, and streaming strategies.
  </li>
  <li>
   You are proficient with workload orchestrators like Slurm, Kubernetes, or Ray, having used them to schedule and manage complex, concurrent training jobs at scale.
  </li>
  <li>
   You understand GPU architecture at a low level: memory hierarchies, warp execution, and what makes a GPU suited for training versus inference workloads.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Join Helsing and work with world-leading experts in their fields
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Helsing&rsquo;s work is important. You&rsquo;ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns.
  </li>
  <li>
   The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world.
  </li>
  <li>
   Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defence industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward.
  </li>
  <li>
   In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts.
  </li>
  <li>
   We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practise responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn&rsquo;t work, and to take ownership of aspects of our culture that you care deeply about.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We Offer
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive salary and VSOP options
  </li>
  <li>
   Relocation support: up to &euro;2,500 and 4 weeks temporary accommodation
  </li>
  <li>
   Learning: &euro;500/&pound;450 yearly allowance
  </li>
  <li>
   Health &amp; wellness: gym membership and mental health support (Nilo.health)
  </li>
  <li>
   Social: regular company events and monthly social allowances
  </li>
  <li>
   Enhanced parental leave: 22 weeks fully paid for primary caregivers &amp; 6 weeks for secondary caregivers
  </li>
  <li>
   Family support: 5 days of paid family emergency leave, 100% remote work option during pregnancy and phased return to work
  </li>
  <li>
   A hands-on onboarding program (affectionately labelled &ldquo;AI-duction&rdquo;), in which you will be familiarising yourself with our tools and ML pipelines used across the company. This is your opportunity to learn our tech stack, explore the company, and learn how we get things done - all whilst working with other AI and engineering teams from day one
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  These are the core benefits across all locations, there may be additional benefits in certain locations.
  <br/>
  <br/>
 </em>
 <em>
  Helsing is an equal opportunities employer. We are committed to equal employment opportunity regardless of race, religion, sexual orientation, age, marital status, disability or gender identity. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation.
  <br/>
  <br/>
 </em>
 Helsing's Candidate Privacy and Confidentiality Regime can be found here.
 <br/>
 <br/>
</div>


AI Research Engineer - ML Engineering

Autodesk

<div>
 <strong>
  Job Requisition ID #
  <br/>
  <br/>
 </strong>
 26WD100236
 <br/>
 <br/>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 <strong>
  Position Overview
  <br/>
  <br/>
 </strong>
 The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world.
 <br/>
 <br/>
 As a Machine Learning Engineer at Autodesk Research, you will work side-by-side with researchers and engineers to build and enable ML-powered capabilities in Autodesk products. You are an ML engineer with strong software engineering skills who is passionate about solving problems and building things, and excited to collaborate with AI researchers to implement generative AI features. You will operate in a fast-moving, research-driven environment where problems are often not fully defined, requiring strong problem framing and rapid iteration.
 <br/>
 <br/>
 The team work in a hybrid working model from our offices in London.
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Collaborate on projects at the intersection of research and product with a diverse, global team
  </li>
  <li>
   Build and iterate on ML pipelines, prototypes, and evaluation workflows, enabling rapid deployment and testing of experimental models
  </li>
  <li>
   Work with complex datasets and representations for model training, evaluation, and analysis
  </li>
  <li>
   Analyze errors and provide solutions to problems
  </li>
  <li>
   Present results to collaborators and leadership
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Minimum Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   BSc or MSc in Computer Science, or equivalent industry experience
  </li>
  <li>
   3+ years of machine learning experience
  </li>
  <li>
   Experience working in research or experimental environments with evolving requirements
  </li>
  <li>
   Proficiency with modern deep learning libraries and frameworks (PyTorch, HuggingFace)
  </li>
  <li>
   Experience with computational geometry and 3D data (e.g., meshes, B-Rep models)
  </li>
  <li>
   Experience working with diverse data representations, including 2D and 3D geometry
  </li>
  <li>
   Experience with version control, reproducibility, and deploying machine learning models
  </li>
  <li>
   Experience using modern AI/GenAI tools in development or experimentation workflows
  </li>
  <li>
   Excellent written documentation skills
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Advanced degree (MSc/PhD) in Machine Learning, Computer Science, or related field
  </li>
  <li>
   Experience scaling machine learning training and data pipelines (e.g., using Ray or similar frameworks)
  </li>
  <li>
   Experience with cloud services and architectures (e.g. AWS, Azure)
  </li>
  <li>
   Experience with LLMs or generative AI systems (fine-tuning, prompting, evaluation)
  </li>
  <li>
   Knowledge of the design, manufacturing, AEC, or media &amp; entertainment industries
  </li>
  <li>
   Experience with Autodesk or similar products (CAD, CAE, CAM, etc.)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Learn More
   <br/>
   <br/>
  </strong>
 </strong>
 <strong>
  About Autodesk
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 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!
 <br/>
 <br/>
 <strong>
  Salary transparency
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 <strong>
  Belonging
  <br/>
  <br/>
 </strong>
 We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging
 <br/>
 <br/>
 <strong>
  Are you an existing contractor or consultant with Autodesk?
  <br/>
  <br/>
 </strong>
 Please search for open jobs and apply internally (not on this external site).
</div>


Machine Learning Engineer 3D Geometry/ Multi-Modal

International SOS

<div>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 We are looking for an experienced Senior Machine Learning Engineer to join our Product team, in Chiswick, West London,
 <br/>
 <br/>
 You will be responsible for building production-grade AI capabilities across the platform&rsquo;s generative and agentic paradigms &ndash; from retrieval-augmented knowledge assistants and context-aware responses to multi-step agent workflows. The role combines strong machine learning and software engineering skills to deliver grounded, governed, and scalable solutions that move from Lab prototype to Factory production.
 <br/>
 <br/>
 This is an excellent opportunity for an experienced engineer, looking for their next move in a global organization.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and implement ML, generative, and agentic AI solutions &mdash; RAG pipelines, prompt workflows, tool-calling agents, and predictive models
  </li>
  <li>
   Build grounded retrieval over enterprise knowledge with source citation and tenant isolation
  </li>
  <li>
   Integrate models via the model gateway, applying guardrails, PII redaction, and content safety on every request
  </li>
  <li>
   Develop and maintain agent orchestration, memory, and human-in-the-loop escalation paths
  </li>
  <li>
   Perform data preprocessing, feature engineering, prompt design, and evaluation using enterprise datasets
  </li>
  <li>
   Deploy solutions through MLOps/LLMOps pipelines with monitoring, evaluations, and SLAs
  </li>
  <li>
   Optimise models and prompts for accuracy, latency, cost, and groundedness
  </li>
  <li>
   Run experiments, track metrics against golden sets, and iterate to improve quality
  </li>
  <li>
   Collaborate with AIOps and Security to integrate solutions into CI/CD and production monitoring
  </li>
  <li>
   Support responsible-AI practices, model cards, and version control for every release
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About You
  <br/>
  <br/>
 </strong>
 6+ years in AI/ML engineering or applied machine learning
 <br/>
 <br/>
 Strong Python skills with scikit-learn, TensorFlow, PyTorch, or XGBoost, plus experience with LLM frameworks (LangChain/LangGraph) and RAG
 <br/>
 <br/>
 Experience with cloud AI services (AWS Bedrock/SageMaker, Azure, or GCP) and vector stores
 <br/>
 <br/>
 Proficiency in SQL and working with data warehouses/lakes and embeddings
 <br/>
 <br/>
 Familiarity with MLOps/LLMOps, containerisation (Kubernetes), and CI/CD
 <br/>
 <br/>
 Understanding of prompt engineering, evaluation harnesses, and guardrails
 <br/>
 <br/>
 Strong grasp of ML theory, software engineering practices, and version control (Git)
 <br/>
 <br/>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive salary and incentive scheme
  </li>
  <li>
   Warm, supportive, and open company culture
  </li>
  <li>
   An opportunity to thrive in a global environment
  </li>
  <li>
   Hybrid working: 3 days in the office
  </li>
  <li>
   Birthday holiday and option to purchase additional annual leave
  </li>
  <li>
   Comprehensive Benefits Package: Private Pension, Private Medical Insurance, Life Assurance and more
  </li>
 </ul>
</div>


Xantura Limited

<div>
 <p>
  <strong>
   Department:
  </strong>
  Platform Delivery
 </p>
 <p>
  <strong>
   Location:
  </strong>
  London
 </p>
 <p>
  <strong>
   Compensation:
  </strong>
  &pound;50,000 - &pound;70,000 / year
  <br/>
  <br/>
 </p>
 <strong>
  Description
  <br/>
  <br/>
 </strong>
 In this role you will work in the Platform team &ndash; a function for the deployment and evolution of the backend platform that underpins the core of the Xantura business.
 <br/>
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Own and advance a predictive modelling platform that scales across problem types and tenants, using it to design, implement, and iterate models (embedding-based sequence encoders, temporal survival models, gradient-boosted decision trees) that predict key vulnerabilities in housing, health, and other social domains.
  </li>
  <li>
   Track developments in ML and frontier models, running structured experiments to bring promising techniques into production safely.
  </li>
  <li>
   Build robust evaluation pipelines, training datasets, and model infrastructure to support continuous improvement of natural language &amp; predictive analytics.
  </li>
  <li>
   Ensure responsible AI deployment, embedding ethical and regulatory considerations into every stage of development.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Skills, Knowledge &amp; Expertise
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Machine Learning, or a related technical field &ndash; or equivalent practical experience.
  </li>
  <li>
   3+ years of professional experience as an ML Engineer, or related role.
  </li>
  <li>
   Strong programming skills and production experience in Python.
  </li>
  <li>
   Experience building and maintaining data or ML pipelines with an orchestration tool such as Dagster (or Airflow, Prefect, etc.).
  </li>
  <li>
   Hands-on experience with common ML libraries and frameworks, e.g. PyTorch, scikit-learn, and gradient-boosting libraries such as XGBoost or LightGBM.
  </li>
  <li>
   Clear evidence of practical experience defining and deploying containerised systems, i.e.:
   <ul>
    <li>
     Implementing APIs for internal services, e.g. via FastAPI;
    </li>
    <li>
     Deploying containerised systems to production, in particular via Kubernetes.
     <br/>
     <br/>
    </li>
   </ul>
  </li>
 </ul>
 <strong>
  <br/>
  In addition, the following would be an advantage:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   PhD in Computer Science, Machine Learning, or a related field with a strong publication record in text analytics, representation learning, or applied predictive modelling.
  </li>
  <li>
   Practical experience productionising LLMs, i.e.:
   <ul>
    <li>
     Working with vector databases and developing retrieval-augmented generation (RAG) pipelines &ndash; experience setting up/configuring vector DBs, as well as using, would be advantageous;
    </li>
    <li>
     Finding and productionising recent AI models (e.g. via Huggingface (transformers), OpenAI APIs);
    </li>
    <li>
     Building agentic systems (e.g. via LangChain, AutoGen, PydanticAI).
    </li>
   </ul>
  </li>
  <li>
   Evidence of participating in Open-Source Software (OSS) development, public hackathons, or other sharable coding samples.
  </li>
  <li>
   Deep expertise in embedding-based architectures, including bi-encoders, cross-encoders, etc. for long-horizon text or temporal prediction tasks.
  </li>
  <li>
   Practical experience building and serving production-ready, asynchronous APIs for embedding and/or other compute-intensive services.
  </li>
  <li>
   Proficiency in Python for building high-performance data and model pipelines, with strong software engineering discipline (testing, versioning, CI/CD).
  </li>
  <li>
   Good familiarity with the Azure ecosystem (Azure Kubernetes Service, Azure Batch, Azure AI Foundry, Azure Machine Learning, Azure Blob Storage, Azure Key Vault) .
   <br/>
  </li>
 </ul>
 This is a Hybrid opportunity with the expectations of being in the office 1 - 2 days a week.
 <br/>
 <br/>
 <strong>
  Job Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive salary reviewed annually
  </li>
  <li>
   Work for a passionate, mission-driven company solving society&rsquo;s big problems
  </li>
  <li>
   Work flexible hours around life commitments with a focus on delivering company value rather than hours worked
  </li>
  <li>
   Training and development opportunities
  </li>
  <li>
   25 days annual leave (plus bank holidays)
  </li>
  <li>
   Company pension
  </li>
  <li>
   Private medical insurance
  </li>
  <li>
   Generous enhanced parental leave policies
  </li>
  <li>
   Cycle to work scheme
  </li>
  <li>
   Flu Vaccinations,
  </li>
  <li>
   Eye Test and contribution towards Glasses for VDU use
  </li>
  <li>
   Employee Assistance Programme
   <ul>
    <li>
     Mental health and wellbeing support
    </li>
    <li>
     Remote GP access
    </li>
    <li>
     Counselling/therapy
    </li>
    <li>
     Physiotherapy
    </li>
    <li>
     Medical second opinions
     <br/>
    </li>
   </ul>
  </li>
 </ul>
</div>


Machine Learning Engineer

Gensler

<div><div><div><div><h2 class="jobSectionHeader"><b>General Information</b></h2>
</div></div><div><div><div><div>Posting Date</div>
<div>08-28-2026</div>
</div><div><div>Time Type</div>
<div>Full-Time</div>
</div><div><div>Job ID</div>
<div>8940</div>
</div><div><div>Areas of Expertise</div>
<div>Design Technology</div>
</div><div><div>Job Category</div>
<div>Data Apps</div>
</div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>Locations</b></h2>
</div></div><div><div><div><div>London, United Kingdom</div>
</div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>Description</b></h2>
</div></div><div></div><div><div><div><div><p>Placed at the heart of Gensler&rsquo;s People + Process + Technology, the Global Design Technology Studio is advancing a growing data and machine learning foundation that is shaping how the firm designs and delivers its work for generations to come. We believe that when the right intelligence is in the hands of the right people at the right moment, we can transform Gensler and our industry so that our designers can make better decisions, unlock new value for clients, and create built environments that are more responsive, more meaningful, and more impactful than ever before.
</p><p>In the role of Machine Learning Engineer, you will drive and operationalize machine learning across AEC data domains including BIM, geospatial, design-performance, operational, and other project and practice data, translating technical capability into tools and workflows that practitioners can use. This is a digitally transformative, hands-on engineering role focused on building, deploying, maintaining, and optimizing machine learning systems and data pipelines, working with large-scale datasets to power production-ready intelligent systems and drive scalable outcomes across the firm. Success in this role means delivering reliable, secure, and well-governed ML systems that integrate into design workflows, are adopted by teams, and improve decision-making across the firm. You will help shape these capabilities inside an established Design Technology team, working alongside AI and data engineers, data scientists, designers, and product stakeholders to translate ambitious, pioneering ideas into production-ready platforms.<br>
</p><p></p><br>
<p><b>What You Will Do
</b></p><div><ul><li>Design, build, and maintain reliable Azure-based ETL/ELT pipelines that deliver clean, documented data to models, APIs, internal applications, dashboards, and Gensler IP.</li>
<li>Own the production ML lifecycle on Azure &mdash; deployment, monitoring, versioning, retraining, rollback, and incident response &mdash; including model registries, feature stores, evaluation frameworks, and benchmarking.</li>
<li>Implement CI/CD, testing, reproducibility, and deployment standards for model and data workflows.</li>
<li>Extend and mature cloud data architecture and modeling strategies that support analytics and machine learning workloads.</li>
<li>Source, profile, and document datasets with business owners to confirm provenance, quality, fitness for use, and alignment with client-data and governance requirements.</li>
<li>Evaluate model performance and address root causes across data quality, feature engineering, training methodology, and architecture.</li>
<li>Translate research prototypes and experimental models into documented, production-ready systems.</li>
<li>Work across AEC data types such as BIM/Revit/IFC, geospatial, design-performance, occupancy, and other built-environment datasets.</li>
<li>Integrate machine learning outputs into design and delivery workflows so practitioners can access insights earlier and make more informed project decisions.</li>
<li>Apply responsible AI and data governance practices, including transparency, traceability, human oversight, and appropriate handling of client and project data.</li>
<li>Support the firm's data-driven design community through technical guidance, code review, and knowledge sharing.</li>
<li>Help define and track success criteria for deployed systems, including reliability, adoption, reuse, and measurable workflow or decision impact.</li><br>
</ul></div><p></p><br>
<p><b>Your Qualifications
</b></p><div><ul><li>Bachelor's or advanced degree in Computer Science, Software Engineering, Data Science, Statistics, Applied Mathematics, or a related field; equivalent production ML or data engineering experience considered.</li>
<li>8+ years of hands-on experience building, deploying, and operating production ML systems on Azure, with practical MLOps and CI/CD experience including experiment tracking, deployment hygiene, monitoring, evaluation, and operational documentation.</li>
<li>Strong Python and software engineering fundamentals, including testing, version control, code review, reproducibility, modular design, documentation, and maintainable code practices.</li>
<li>Strong experience with Azure-based data and ML platforms, ideally including Azure ML, Databricks, Azure Data Factory or Fabric pipelines, Blob/Data Lake storage, and MLflow or similar tooling.</li>
<li>Experience building production-grade ETL/ELT pipelines and supporting ML workloads from ingestion through deployment.</li>
<li>Comfort moving between data engineering, machine learning, cloud architecture, infrastructure, and hands-on data exploration in a creative, collaborative environment.</li>
<li>Practical knowledge of containerization, infrastructure-as-code, and platform and tooling decisions in lean or fast-moving engineering environments.</li>
<li>Clear communicator who can explain technical decisions to non-engineering stakeholders, collaborate across disciplines, and mentor or support junior engineers.</li>
</ul></div><p>Meaningful pluses
</p><div><ul><li>Experience with AEC, real estate, BIM, geospatial, or digital twin data</li>
<li>Experience integrating ML into practitioner-facing workflows</li>
<li>Familiarity with responsible AI practices</li>
<li>LLM or GenAI deployment patterns</li>
<li>Power BI or other visualization tools</li>
<li>Experience with agentic engineering practices</li><br>
</ul></div><p></p><br>
<p><b>Life at Gensler
</b></p><p>At Gensler, we are as committed to enjoying life as we are to delivering best-in-class design. From curated art exhibits to internal design competitions to &ldquo;Well-being Awareness Week,&rdquo; our offices reflect our people&rsquo;s diverse interests.
</p><p>We encourage every person at Gensler to lead a healthy and balanced life. Our comprehensive benefits include medical, dental, vision, disability, wellness programs, flex spending, paid holidays, and paid time off. We also offer a 401k, profit sharing, employee stock ownership, and twice annual bonus opportunities. Our annual base salary range has been established based on local markets.<br>
<br>
</p><p>As part of the firm&rsquo;s commitment to licensure and professional development, Gensler offers reimbursement for certain professional licenses and associated renewals and exam fees. In addition, we reimburse tuition for certain eligible programs or classes. We view our professional development programs as strategic investments in our future.</p><br>
<div></div>
<div></div><br>
<div><b>NOTICE TO APPLICANTS
</b></div><div>We are proud to be an Equal Employment Opportunity and Affirmative Action employer of choice. All aspects of employment decisions will be based on merit, performance, and business needs. We do not discriminate on the basis of any status protected under applicable regulatory laws.
</div><div>Individuals with disabilities and protected veterans are encouraged to apply. We also consider qualified applicants with criminal histories consistent with applicable regulatory laws.
</div><div>Gensler endeavors to make gensler.com/careers accessible to all applicants. If you need assistance or an accommodation due to a disability, you may <b>contact us </b>.
</div><div>Regarding Gensler&rsquo;s approach to recruiting new talent, we will never ask an applicant for sensitive or personal financial information during the recruitment process. We advise all applicants seeking employment with Gensler to review available information on <b>recruitment fraud </b>. Anyone who suspects that they have been contacted by someone falsely representing Gensler should email talentacquisition@gensler.com .</div></div></div></div></div></div></div>

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  JOB DETAILS
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  Role Title: AI Engineer
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  Must have skills:
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  &bull; Proven experience as an AI, Machine Learning, or Privacy Engineer.
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  &bull; Proficiency in programming languages such as Python is added advantage.
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  &bull; Experience with deep learning frameworks like TensorFlow, PyTorch, or JAX.
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  &bull; Experience working with multi-cloud technologies. GCP is mandatory.
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  &bull; Excellent analytical and communication skills, with the ability to explain complex technical and privacy concepts to non-technical stakeholders
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  &bull; Experience with adversarial testing and robustness evaluation of AI models.
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  &bull; Experience in the end-to-end development of AI/ML models and applications.
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  &bull; Ability to lead and train the team on model training
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  <br/>
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  Minimum number of relevant years of experience: 8-10
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</div>


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