machine learning engineer

senior software engineer

senior data scientist

senior data engineer

senior ai engineer

ai ml computational science senior manager

Talan

<div><b>Company Description</b><p><br>
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI).</p><b><br>
Job Description</b><p><br>
As our AI practice grows, we are looking for a capable, hands-on AI Engineer to help build and deliver the solutions at the heart of our client work. Coming from a data science background, you are equally comfortable applying proven machine-learning techniques to traditional analytics problems and working with the latest generative AI (large language models, retrieval-augmented generation, and agent-based applications). You enjoy building, you write dependable code, and you turn well-defined designs into working software.</p><p>
This is a delivery-focused role that sits a level below our Lead Data Scientists. You will own meaningful workstreams within a project rather than the whole engagement, working to an architecture and plan shaped by more senior colleagues. In return, you will gain breadth across modern AI, exposure to real client problems,</p><p>
You will also be a supportive presence within the team, helping your peers solve problems, sharing what you learn, and giving day-to-day guidance to graduate and junior resources working alongside you.</p><p><b>
Required skills &amp; experience:</b></p><ul><li>
Build, test, and deploy AI and machine learning components within client projects to the standards and designs set by senior colleagues.</li><li>
Develop GenAI and LLM-based features (prompting, retrieval-augmented generation, and simple agentic workflows) alongside more traditional ML models.</li><li>
Deliver classical data science tasks (data preparation, feature engineering, model training, and evaluation) on projects that call for them.</li><li>
Translate solution designs into clean, well-documented, production-minded code.</li><li>
Contribute to model evaluation, testing, and monitoring.</li><li>
Support and guide very junior and graduate resources, reviewing their work and helping them grow.</li><li>
Help peers unblock technical problems and share knowledge across the team.</li><li>
Take part in client and team discussions and communicate your work clearly.</li></ul><br>
<b>
Qualifications</b><p><b><br>
To qualify for this role, you must have:
</b></p><ul><li>Typically, 2&ndash;4 years' experience in data science, machine learning, or AI engineering.</li><li>
Solid grounding in core data science and machine learning.</li><li>
Practical experience with LLMs and generative AI, including prompting and RAG.</li><li>
Familiarity with how AI agents are built and orchestrated.</li><li>
Strong Python and common data/ML libraries; good engineering habits.</li><li>
Clear communicator and collaborative team player.</li></ul><p><b>
Ideally, you&rsquo;ll also have, but not essential:</b></p><ul><li>
Exposure to cloud AI platforms, Azure a plus.</li><li>
Experience practicing MLOps and LLMOps.</li><li>
Early experience mentoring junior colleagues.</li><li>
Interest in consulting and client-facing delivery.</li></ul><p><b>
You must be:</b></p><ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul><p>
#TalanUK #LI-HB1</p><b><br>
Additional Information</b><p><b><br>
Compensation &amp; Benefits Package:</b></p><ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul><p><b>
Why join:</b></p><p>
This is a role built for momentum, working across the full spectrum of modern AI, learning from senior architects and leads on real engagements, with genuine responsibility from day one and a clear path into a leadership track.</p></div>

AI Engineer (LLMs, Agents & Applied Data Science)

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

Hiscox

<div>
 <strong>
  Job Type
  <br/>
  <br/>
 </strong>
 Permanent
 <br/>
 <br/>
 <strong>
  Build a brilliant future with Hiscox
  <br/>
  <br/>
 </strong>
 <strong>
  Reporting to: Re &amp; ILS Head of Data
  <br/>
  <br/>
 </strong>
 <strong>
  Location:
 </strong>
 London
 <br/>
 <br/>
 Type: Permanent
 <br/>
 <br/>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 The Lead Data Scientist is a crucial member of the
 <strong>
  extended
 </strong>
 RE&amp;ILS Tech Leadership Team, responsible for building, leading, and nurturing a highly capable (New)
 <strong>
  Data Science and Machine Learning
 </strong>
 chapter.
 <br/>
 <br/>
 This role facilitates the successful delivery of new AI Cloud-based solutions against our growing list of business use cases (involving complex Data Analytics, Machine Learning, and AI Agent based solutions).
 <br/>
 <br/>
 You will co-lead the new Data Science chapter with the RE&amp;ILS Head of Data and help ensure its members provide Data Science capabilities and insights to support decision-making across RE&amp;ILS strategic Value Streams. Whilst the chapter grows, you are expected to be
 <strong>
  hands-on
 </strong>
 actively helping to architect, design, and build AI or Data Science-based solutions, using internally trained models, LLMs and/or a combination of both.
 <br/>
 <br/>
 Whilst undertaking this pioneering work it is essential that you and your entire chapter operates within the boundaries of the
 <strong>
  Group AI Governance Framework
 </strong>
 and maintains rigorous data governance standards. You will be accountable of this adherence.
 <br/>
 <br/>
 This is likely to be your first managerial role and the first time you have had one or more direct reports &ndash; having previously been a Senior Data Scientist or Machine Learning Engineer yourself. In this role you will be responsible for the management of a 1 to 4 junior and mid-level Hiscox FTEs and Partner resources too. You will be expected to support the Head of Data with attracting and retaining the best talent; helping to manage their career progression and ensure they are highly engaged, find the work fulfilling, and have the ability to rapidly deliver value to the business. As this is likely to be your first managerial role you will be supported and guided by other Data Leaders &ndash; Head of Data and the Hiscox Group Head of Data Science as well.
 <br/>
 <br/>
 <strong>
  About Hiscox Re &amp; ILS
  <br/>
  <br/>
 </strong>
 Hiscox Re &amp; ILS is located in
 <strong>
  Bermuda and London
 </strong>
 and underwrites reinsurance risks from around the world on behalf of our own and other people&rsquo;s capital. The team of over 100 smart, enthusiastic individuals are committed to providing top quality service to brokers and clients across a broad range of reinsurance products. Our approach is simple; match the best underwriting risk against globally diversified capital. Our proactive, product-led underwriting approach is complemented by a commitment to world class service and purpose-built analytics and systems. We know our people are our biggest asset so finding and retaining the best talent is critical to achieving our vision.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Chapter Leadership &amp; Talent Management
  </li>
  <li>
   People Management: Lead, recruit, mentor, coach, train, and retain a high-performing chapter of Data Scientists and Machine Learning Engineers (expected to grow to over the next few years), including both Hiscox FTE and Partner colleagues. Inspire chapter members to be curious, embrace new ideas, and nurture psychological safety to help build a high-performance culture.
  </li>
  <li>
   In this role you will manage at least one to two Hiscox data scientists and some partner resources too. You will be expected to manage their performance with relevant PDRs and help to calibrate their overall performance ratings with other people managers in the team. You will work with the Head of Data and Group Head of Data Science to help tailor the training needs to suit each individual and ensure they have the opportunity to grow and progress in their chosen career paths.
  </li>
  <li>
   Culture &amp; Development: Cultivate a collaborative, engaged, and fulfilled team culture. Provide technical leadership, career guidance, and direction to the team, ensuring successful delegation to all chapter members.
  </li>
  <li>
   Best Practice: Ensure the chapter adheres to best practices in data science, AI, and complex analytics, sharing knowledge across the wider Hiscox Analytics and Data community through active participation in Communities of Practice.
  </li>
  <li>
   Mentoring: Mentor and educate others in the various data science techniques, encouraging the team to continually learn &ndash; especially supporting the adoption of LLMs and proprietary models that could significantly accelerate our ability to deploy value.
  </li>
  <li>
   Solution Delivery &amp; ML Ops Excellence
  </li>
  <li>
   Hands-On Architecture: Get hands-on to help architect, design, and build complex models that integrate into existing IT solutions to improve data-driven decision-making throughout the Reinsurance Value Chain. Ensure you and your chapter members work closely with Platform Engineers and Architects to create the most optimal and safe solutions.
  </li>
  <li>
   ML Ops Platform: Actively work with the Head of Platform Engineering to establish and maintain a professional ML Ops platform to facilitate the effective support of developed models in production. This includes embedding a rigorous model evaluation process, ensuring consistent model refresh/rebuild capabilities due to model or data drift, and implementing effective monitoring and alerts against rogue behaviour.
  </li>
  <li>
   Speed of Execution: Empower the chapter to work effectively within autonomous squads, delivering desired and valuable outcomes in an incremental manner while correctly balancing accuracy, fast return on investment, and reliability. Understand when to move on and fail fast &ndash; as a lot of AI use cases will be highly experimental in nature with no guarantees of success.
  </li>
  <li>
   Pipeline Collaboration: Work with Data Engineering and other teams to properly understand and contribute to the requirements and building of necessary data pipelines/products consumed by our models.
  </li>
  <li>
   Strategy, Governance &amp; Innovation
  </li>
  <li>
   Use Case Identification: Continually work with key business leaders, the Head of Data and key stakeholders to identify new use cases and opportunities where data science/AI can deliver a competitive advantage or reduce waste/costs through efficiency gains.
  </li>
  <li>
   Governance &amp; Compliance: Champion data and model governance, working within the Group AI Governance Framework. Ensure a mature understanding of data governance, lineage, and version control, and enforce data privacy by design in all new work.
  </li>
  <li>
   Innovation: Maintain a strong awareness of new trends and techniques in Data Science, AI, and Machine Learning. Drive the identification of innovative data solutions and technologies, and actively undertake Proof of Concepts and R&amp;D to deliver reliable insights and potential next steps quickly.
  </li>
  <li>
   Communication: Ensure clear and effective communication of data science solutions and outcomes across business layers, technical teams, and senior leadership.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Experience And Structure
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Reporting: Reports into the RE&amp;ILS Head of Data with a dotted line into the new Group Head of Data Science.
  </li>
  <li>
   Direct Reports: Direct line management for Data Scientists and Machine Learning Engineers within the RE&amp;ILS Data Science Chapter.
  </li>
  <li>
   Key Partners: RE&amp;ILS CTO, Group Head of Data Science, RE&amp;ILS Head of Data, Product Managers, Product Owners, and strategic partners (e.g. Google Cloud, Microsoft).
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Candidate Profile
  <br/>
  <br/>
 </strong>
 The successful candidate will be an energetic, highly capable, and passionate Senior Data Scientist who wants to move into their first people management role. You will need to balance technical expertise with effective people management and strategic business partnership. You must be comfortable working in an FCA-regulated business, advocating for a data-driven approach, and driving innovation while maintaining rigorous AI governance standards. You will have a strong determination and resilience and not fear failure or the inevitable setbacks often found in highly experimental work.
 <br/>
 <br/>
 <strong>
  Main Experience Required Is
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Deep Interest in Leadership: As an experienced data scientist or machine learning engineer, has previously demonstrated excellent traits in mentoring and coaching more junior team members and has been happy to invest in them - clearly demonstrating they care about other peoples&rsquo; career progression. Also you can evidence some successful business outcomes that you personally drove forward using advanced Data Science/AI &ndash; as this most likely is your first leadership role.
  </li>
  <li>
   Technical Depth: Extensive "hands-on" experience in architecting, designing, and building complex ML models, with a strong understanding of cloud services and the AI/ML/LLM ecosystem.
  </li>
  <li>
   ML Ops Maturity: Proven ability to build, maintain, and support production-deployed models, including establishing effective monitoring, evaluation, and refresh processes.
  </li>
  <li>
   AI and Data Governance: Mature understanding of AI and Data governance - data obfuscation &amp; data privacy laws, data version control, data lineage, and the application of AI governance frameworks in a regulated environment.
  </li>
  <li>
   Stakeholder Management: Experience in managing and driving collaboration with business unit leaders (Underwriters, pricing teams, MI team) and external technology partners like Google Cloud, Snowflake, DataIku and Microsoft.
  </li>
  <li>
   Education: Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent.
  </li>
  <li>
   Capacity for independent, high-quality research and exploratory data analysis, with the ability to develop and apply novel methodologies to solve ill-defined and challenging business problems.
  </li>
  <li>
   Exceptional proficiency in Python (and R) for data science, coupled with SQL capabilities for data manipulation and extraction. Demonstrable mastery in a wide range of machine learning and statistical modelling techniques, from classical linear models and tree-based methods to advanced deep learning architectures.
  </li>
  <li>
   Real world experience with, or demonstrable capability for, applications of Generative AI, Large Language Models (LLMs), AI Agents and related areas such as Natural Language Processing (NLP) or Computer Vision, relevant to business solutions.
  </li>
  <li>
   Demonstrate a Solid understanding of foundational statistics and experimental design. Pioneer the development and robust deployment of highly impactful machine learning and AI-driven solutions, directly contributing to significant commercial value, quantifiable business growth, or efficiency gains across the organization.
  </li>
  <li>
   Ability to translate complex data science insights into tangible, measurable improvements across critical business processes and key performance indicators, ensuring the real-world adoption and beneficial outcomes of our analytical work.
  </li>
  <li>
   Ability to elevate the technical maturity and capabilities of the data science chapter by shaping and implementing industry-leading AI, data, and analytics techniques, methodologies, and engineering best practices.
  </li>
  <li>
   Educator: shown the ability to train and coach more junior and mid-level team members - ensuring they have excellent career progression and become high performers.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 If you are a visionary expert looking for your first leadership role and ready to accelerate our value delivery and champion all things Data Science and AI, we invite you to apply for the position of Lead Data Scientist at Hiscox Re &amp; ILS. Join our team and be a catalyst for AI adoption in a dynamic, forward-thinking organization.
 <br/>
 <br/>
 <em>
  Work with amazing people and be part of a unique culture
 </em>
</div>


Lead Data Scientist

<div><b>Company Description</b><p><br>
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI).</p><b><br>
Job Description</b><p><br>
We are hiring a Lead Data Scientist to drive the technical delivery of our most demanding AI engagements and to lead a growing team of data scientists and AI engineers. This role is for a practitioner who is equally fluent in the rigour of traditional data science (statistical modelling, machine learning, experimentation) and the fast-moving world of large language models and agentic AI. You understand that the best solutions often combine both.</p><p>
You will own delivery from problem framing through to deployment, ensuring the work is technically sound, commercially valuable, and aligned to the architectural vision. As a lead, you will mentor the team, raise engineering and modelling standards, and act as a trusted technical partner in client conversations. You will help clients see not just what is possible, but what is practical and worth doing.</p><p>
This is a delivery-focused leadership role with genuine breadth: one week you might be tuning a forecasting model, the next designing an agentic workflow or evaluating an LLM pipeline for a client pilot.</p><p><b>
Required skills &amp; experience:</b></p><ul><li>
Lead end-to-end delivery of data science and AI projects, owning technical quality and outcomes.</li><li>
Combine classical ML (regression, classification, forecasting, optimisation) with modern GenAI, LLM, and agent-based approaches as the problem demands.</li><li>
Mentor and develop data scientists, AI engineers, and junior consultants, growing the team's capability.</li><li>
Translate business problems into well-scoped analytical and AI solutions and communicate results to non-technical stakeholders.</li><li>
Ensure best practice across the AI lifecycle &mdash; experimentation, evaluation, testing, deployment, and monitoring.</li><li>
Act as the bridge between architecture and delivery, ensuring implementation stays faithful to design.</li><li>
Support pre-sales and client discussions with credible technical input and realistic estimation.</li><li>
Champion reproducibility, model governance, and responsible practice in everyday delivery.</li></ul><br>
<b>
Qualifications</b><p><b><br>
To qualify for this role, you must have:
</b></p><ul><li>Minimum 5 years in data science or AI delivery, including hands-on leadership of technical teams or workstreams.</li><li>
Strong foundations in machine learning and statistics, with demonstrable production experience.</li><li>
Practical experience with LLMs and generative AI &mdash; prompting, RAG, fine-tuning, and evaluation.</li><li>
Exposure to AI agents and orchestration frameworks, and an appetite to deepen it.</li><li>
Proficiency in Python and the modern data / ML stack; sound data engineering instincts.</li><li>
Excellent communication and stakeholder skills, ideally in client-facing or consulting settings.</li></ul><p><b>
Ideally, you&rsquo;ll also have, but not essential:</b></p><ul><li>
Familiarity with the Azure AI ecosystem (Azure ML, Azure OpenAI, Databricks / Fabric).</li><li>
Experience supporting business development or pre-sales.</li><li>
Domain depth in a regulated or data-rich industry.</li><li>
Contributions to open source, publications, or a visible professional profile.</li></ul><p><b>
You must be:</b></p><ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul><p>
#TalanUK #LI-HB1</p><b><br>
Additional Information</b><p><b><br>
Compensation &amp; Benefits Package:</b></p><ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul><p><b>
Why join:</b></p><p>
You will lead substantive, end-to-end AI work in a practice that is scaling fast and backing its people to grow with it. You will shape how a team works, influence how clients adopt AI, and keep your own skills at the frontier, bridging proven data science with the most current GenAI and agentic techniques. It is an opportunity to lead, deliver, and keep building.</p></div>

Lead Data Scientist (Classical ML, LLMs & AI Agents)

Alignerr

<div>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 What if your machine learning expertise could directly influence how the most advanced AI systems in the world think, reason, and write code? We're looking for experienced ML engineers in London to evaluate AI-generated machine learning solutions &mdash; catching errors, improving quality, and helping frontier AI models get genuinely better at one of the hardest things they do.
 <br/>
 <br/>
 This is a fully remote, flexible contract role. Work asynchronously on your own schedule, from wherever you are. No fixed hours, no meetings &mdash; just high-impact, expert work that matters.
 <br/>
 <br/>
 <ul>
  <li>
   Organization: Alignerr
  </li>
  <li>
   Type: Hourly Contract
  </li>
  <li>
   Location: Remote (UK-based)
  </li>
  <li>
   Commitment: Flexible, project-based
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What You'll Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Review and evaluate AI-generated machine learning code &mdash; including Python, TensorFlow, PyTorch, and scikit-learn &mdash; for correctness, efficiency, scalability, and clarity
  </li>
  <li>
   Write high-quality ML solutions to modeling, data processing, and deployment problems across a range of difficulty levels
  </li>
  <li>
   Craft clear, developer-friendly explanations for model architecture decisions, code logic, and problem-solving approaches
  </li>
  <li>
   Identify edge cases, ambiguities, and weaknesses in problem statements, datasets, or AI-generated responses
  </li>
  <li>
   Help set the quality bar for how AI understands and produces machine learning code
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Who You Are
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Deeply fluent in machine learning &mdash; you know your way around model development, data preprocessing, training pipelines, and deployment
  </li>
  <li>
   Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
  </li>
  <li>
   Strong written communicator &mdash; able to explain complex ML concepts clearly and precisely
  </li>
  <li>
   Detail-oriented and rigorous &mdash; you catch what others miss and care about getting things right
  </li>
  <li>
   Self-motivated and comfortable working independently in an async environment
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice to Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3&ndash;5+ years working on machine learning projects, pipelines, or MLOps
  </li>
  <li>
   Experience with model evaluation, cloud deployment, or production ML systems
  </li>
  <li>
   Bachelor's, Master's, or PhD in Computer Science, Machine Learning, or a related field
  </li>
  <li>
   Background in data labeling, RLHF, or other AI training workflows
  </li>
  <li>
   Prior experience with code review or technical writing
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Why Join Us
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Work on cutting-edge AI projects alongside leading research labs and top AI teams
  </li>
  <li>
   Fully remote and async &mdash; work when and where it suits you, with no minimum hour commitments beyond project needs
  </li>
  <li>
   Freelance autonomy with the structure of meaningful, task-based work
  </li>
  <li>
   Your contributions directly improve AI models used by top research labs and enterprise teams worldwide
  </li>
  <li>
   High-performing contributors take on expanded responsibilities and lead new programs
  </li>
  <li>
   Potential for ongoing work and contract extension as new projects launch
  </li>
 </ul>
</div>


Software Engineer – Machine Learning (AI Training)

<div><h3 class="jobSectionHeader"><b>Description</b></h3><div><br>
Insurance isn't the first industry most people think of when they imagine interesting data science work. That's exactly why this role is interesting.</div><div>
<br>
CFC's Data &amp; AI unit is building production agentic systems that automate complex underwriting decisions - not demos, not proof-of-concepts sitting on a shelf, but AI agents and Machine Learning (ML) pipelines that drive real business outcomes. The team includes machine learning engineers and software engineers shipping production services, and this role sits alongside them as an analytical counterpart: running experiments, stress-testing assumptions, and generating the evidence that shapes what gets built and how it improves over time.</div><div>
<br>
This is an Associate Data Scientist role designed for someone early in their career who wants genuine exposure to production AI systems from day one. You'll work closely with ML and AI engineers, contributing to discovery work that feeds directly into live services - statistical analysis, feature engineering, LLM evaluation, and the kind of careful, evidence-based thinking that makes the difference between an AI system that works in a notebook and one that holds up under real conditions.<br>
</div><div>The problems are genuinely hard. The data is complex, the decisions are high-stakes, and the domain has the kind of depth that keeps the work interesting. If you want to grow quickly in applied AI and ML - working on real systems, not toy datasets - this is the right environment.</div><h3 class="jobSectionHeader"><b><br>
About the role</b></h3><br>
<ul>
<li>
Design and run experiments that directly shape production AI agents &mdash; testing ideas, validating approaches, and turning research into deployed improvements.</li>
<li>Actively explore cutting-edge developments in AI and machine learning &mdash; with the space and support to experiment, prototype, and bring new techniques into production where they add value.</li>
<li>Evaluate and refine LLM-powered workflows &mdash; building robust evaluation frameworks, stress-testing agent behaviour, and driving continuous quality improvements in live systems.</li>
<li>Explore complex, real-world datasets to uncover insights that meaningfully improve underwriting decisions and system performance at scale.</li>
<li>Prototype and iterate on features for AI/ML pipelines, taking ideas from early exploration through to measurable impact in production services.</li>
<li>Investigate how agentic systems behave in production &mdash; identifying edge cases, failure modes, and opportunities to make systems more robust and reliable.</li>
<li>Collaborate closely with ML/AI engineers to bridge research and production &mdash; contributing code, debugging issues, and helping ship improvements end-to-end.</li>
<li>Document experiments, findings, and methodologies clearly so that insights are reproducible and decisions are traceable.</li></ul><br>
<h3 class="jobSectionHeader"><b>
About you</b></h3><div><br>
We are looking for a Junior Data Scientist who enjoys solving complex problems and turning data into meaningful, real‑world outcomes. In this role, you will work across the full analytical lifecycle, from exploring data and building machine learning models to shaping how insights are communicated and applied across the business. You also play a part in how we responsibly explore and apply emerging technologies such as LLMs, focusing on how they perform and deliver value in practice.<br>
<br>
You:</div><ul>
<li>combine a strong grounding in statistics with hands‑on technical capability in Python and SQL</li>
<li>take pride in producing clear, reliable analysis</li>
<li>are thoughtful and detail‑driven, able to communicate effectively with a wide range of stakeholders, and comfortable learning from others while growing your own ownership</li>
<li>bring curiosity, ask the right questions and look beneath the surface</li>
<li>have experience with Azure, MLflow, or LLM tooling is a bonus, but not expected&mdash;we value mindset and approach just as highly as experience.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Core Values</b></h3><div><br>
<b>
Love what you do:</b><br>
We show up each day ready to take on the world. Our passion and intensity set us apart and makes the difference to our colleagues, customers, brokers and carriers.<br>
<br>
<b>Challenge everything:</b><br>
We&rsquo;re never afraid to question the way that things are done and we constantly challenge ourselves and others to makes things better.<br>
<br>
<b>Have fun, be good:</b><br>
Insurance is a serious business, but we don&rsquo;t take ourselves too seriously. We make it fun to work at CFC, we welcome all viewpoints, and we treat everyone how we would expect to be treated.</div><h3 class="jobSectionHeader"><b><br>
About CFC</b></h3><div>
CFC is a specialist insurance provider, pioneering emerging risk and market leader in cyber. Our global insurance platform uses cutting-edge technology and data science to deliver smarter, faster underwriting and protect customers from today's most critical business risk.<br>
</div><div>Headquartered in London with offices in New York, Melbourne, Sydney, Austin, Madrid, Brussels and Brisbane, CFC has over 1100 staff and is trusted by more than 100,000 businesses across 90 countries.<br>
</div><div>At CFC, insurance isn't just about underwriting. From data science to software development, and digital marketing design, we've got something for everyone. We're passionate about pushing boundaries, thinking differently and building the insurance company of the future.<br>
<br>
CFC is committed to the principles of equal opportunities and creating an environment in which all individuals are always treated with dignity and respect. We encourage a diverse corporate culture of openness and appreciation to create an environment in which your talent can be developed in the best possible way. Should you require any reasonable adjustments at any stage of the recruitment process please let us know.</div></div>

Associate Data Scientist

Wise Australia Investments

<p></p><div><div><div><p>Wise is a global technology company, building the best way to move and manage the world&rsquo;s money.<br>
<b>Min fees. Max ease. Full speed.</b></p><p>
Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.</p><p>
As part of our team, you will be helping us create an entirely new network for the world's money.<br>
<b>For everyone, everywhere.</b></p><p>
.</p><p><b><br>
Job Description</b></p><p><b><br>
About the role:</b></p><p>
Wise moves billions across borders every year. Behind every transaction is a decision: is this safe? Our ML systems make that call - at scale, in real time, across every market we operate in.</p><p>
Our Risk ML team is building the next generation of financial crime detection at Wise - investing in modern architectures like deep learning, graph neural networks, and foundation models to detect increasingly sophisticated fraud and money laundering patterns. We're looking for a Staff Applied ML Engineer to lead this evolution: defining the architecture strategy, shipping production neural models, and building the blueprint that scales across FinCrime domains.</p><p>
This is a greenfield opportunity - you'll be setting the direction for how Wise applies modern ML to financial crime risk, with strong investment and engagement from senior leadership.</p><p><b>
How we work:</b></p><p>
Risk ML sits within Wise's FinCrime organisation, owning the full ML and AI foundation for financial crime detection. We're scaling into three dedicated pillars - Feature Platform, Learning Loop and Risk Modelling. You'll sit in Risk Modelling, working alongside data scientists, platform engineers, product and domain experts.</p><p>
We operate with high autonomy and low hierarchy. You'll own problems end-to-end - from research and architecture decisions through to production deployment and impact measurement. We value engineers who shape direction, not just execute tickets.</p><p><b>
What will you be working on?</b></p><ul><li>
Designing and shipping ML and deep learning models for financial crime detection - sequence-based, graph-based, attention-based - serving real-time decisions at Wise's scale</li><li>
Defining the architecture strategy for how Wise applies modern ML to risk - which model families, which serving patterns, which training paradigms</li><li>
Building the reusable end-to-end pipeline pattern - from experimentation through training to production deployment - that future models follow</li><li>
Evaluating and prototyping foundation model and embedding approaches for transaction representation across FinCrime domains</li><li>
Partnering with Data Science on model evaluation, experimentation design and causal measurement in domains where clean A/B testing isn't always possible</li><li>
Mentoring engineers and data scientists on modern ML fundamentals, production best practices, and architectural decision-making</li></ul><p><b>
What do you need?</b></p><ul><li>
Production experience shipping deep learning models at scale - systems serving real traffic under latency constraints</li><li>
Ability to make architecture-level decisions independently - model selection, training infrastructure, serving strategy - and explain the reasoning and tradeoffs</li><li>
Experience designing ML systems with hard latency and throughput requirements, including optimisation decisions (quantization, pre-computed embeddings, batching strategies)</li><li>
Strong fundamentals in deep learning: gradient dynamics, attention mechanisms, graph message-passing, sequence modelling</li><li>
Track record of influencing technical strategy across teams - you don't just build, you shape direction</li><li>
Python, PyTorch (or equivalent), distributed training, ML pipeline orchestration</li></ul><p><b>
Nice to Have:</b></p><ul><li>
Experience in FinCrime, fraud detection, AML, or regulated financial services</li><li>
Experience with graph-based methods (GNNs, entity resolution, link analysis) in production</li><li>
Foundation model fine-tuning or LLM evaluation experience</li><li>
Experience establishing modern ML practices in organisations scaling their ML capabilities</li></ul><p>
I<b>nterested? Find out more:</b></p><ul><li><p><b>
How we work &ndash; a practical guide</b></p></li><li><p><b>
DEI @ Wise</b></p></li><li><p><b>
Wise Tech Stack (2025 update)</b></p></li><li><p><b>
See what it's like to work at Wise London!</b></p></li><li><p><b>
Our Engineering career map</b></p></li><li><p>
Wise Engineering &ndash;<b> https://medium.com/wise-engineering</b></p></li></ul><p>
What do we offer:</p><ul><li><p>
Starting salary: &pound;145,000 - &pound;182,000 + RSUs</p></li><li><p><b>
Wise Benefits</b></p></li></ul><p>
#LI-AB3 #LI-Hybrid</p><p><b><br>
Additional Information</b></p><div></div><p><br>
For everyone, everywhere. We're people building money without borders &mdash; without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.</p><p>
We're proud to have a truly international team, and we celebrate our differences.<br>
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.</p><p>
If you want to find out more about what it's like to work at Wise visit <b>Wise.Jobs</b>.</p><p>
Keep up to date with life at Wise by following us on </p></div></div><p></p><div><div><div><div><b>Instagram</b></div></div></div></div></div><div></div>

Staff Applied ML Engineer - Financial Crime

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