machine learning engineer

ai engineer

data engineer

senior software engineer

software engineer

deep learning engineer

Accenture

<div>YOU ARE
As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your spans the full solution lifecycle &mdash; assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.
THE WORK<ul><li>
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions</li><li>
Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps &amp; MLOps</li><li>
Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC</li><li>
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites</li><li>
Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production</li><li>
Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools</li><li>
Justify the value of model approaches in business problems</li><li>
Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production</li></ul></div>
 
<div>EDUCATION<ul><li>
Bachelor's Degree or equivalent</li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.</li><li>
Experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming</li><li>
Experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks</li><li>
Experience in building and deploying AI/ML based software to a cloud environment.</li></ul>
PREFERRED QUALIFICATION<ul><li>
Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch).</li><li>
Experience working with language models like LLM's APIs and optimizing their usage for specific applications.</li><li>
Experience with the following programming languages: Python, C++, Java, R, SQL</li><li>
Strong written &amp; verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders</li><li>
Strong client-facing skillsets in a consulting environment</li><li>
Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams</li><li>
Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation</li><li>
MS or PhD in related field preferred (computer science, engineering, etc.)</li></ul></div>

AI/ML Computational Science Manager

iProov

ML Engineer
 About iProov
 iProov provides science-based biometric solutions that enable the world’s most security-conscious organizations to streamline secure remote onboarding and authentication for digital and physical access. Our award-winning liveness technology and iSOC offer unmatched resilience against deepfakes and generative AI threats while ensuring effortless, scalable user experiences. Trusted by leading governments and enterprises, including the U.S. Department of Homeland Security, U.K. Home Office, GovTech Singapore, ING, and UBS, iProov sets the standard in biometric identity assurance.
 This global trust is built not only on our technology but on the strength of the people behind it. For us, diversity at iProov is about reflecting the customers we serve, holding the principles of equality and inclusion at the heart of everything we do and all that we stand for, embracing differences, creating possibilities, and growing together. We aim to foster a culture where individuals of all backgrounds feel confident in bringing their whole selves to work, feel included, and their talents are nurtured, empowering them to contribute fully to our purpose.
 
The Role
 Reports to: Head of Core AI
 Location: WeWork Waterloo - Hybrid
 Comp: Negotiable (Base) + Company Performance Bonus (10%) + Share Options + UK iProov Benefits
 
iProov is looking for a Machine Learning Engineer to join our Core AI team. You will be responsible for working on the biometric systems, developing new techniques and algorithms ensuring security and performance.
 How you can make an impact 
 <ul>
<li>Drive research projects in the areas of computer vision, machine learning and biometrics.</li>
<li>Research new biometric systems and contribute to prototyping new products - by testing and integrating existing technologies or by designing a new solution.</li>
<li>Develop and train deep learning models for face verification, liveness and attack detection.</li>
<li>Improve upon data and evaluation strategies, including synthetic and adversarial data.</li>
<li>Investigate failure modes and improve generalisation, robustness and fairness.</li>
<li>Collaborate cross-functionally to turn models into production-quality services.</li>
</ul>
What we would like to see from you
 <ul>
<li>A Masters or PhD in a numerate discipline such as Computer Science, Engineering, Computational Neuroscience.</li>
<li>Proven proficiency or experience in machine learning and computer vision.</li>
<li>Enjoys collaborating with cross-functional teams.</li>
<li>Proficiency in Python and modern deep learning frameworks.</li>
<li>Strong problem-solving skills and out-of-box thinking.</li>
</ul>
Extras: 
<ul>
<li>Experience working on 0- &gt;1 products.</li>
<li>Experience generating and using synthetic data</li>
</ul>
Benefits
 <ul>
<li>25 days Annual Leave, plus 8 Bank Holidays (more holiday with service - up to an extra 5 days off per year based on your continuous service)</li>
<li>Growth Shares allocated after passing probation (6 months of service)</li>
<li>Salary sacrifice schemes including: Pension, Cycle To Work and Electric Car Scheme</li>
<li>Nursery Sacrifice Scheme</li>
<li>Work Overseas Perk - Work globally for up to 2 weeks</li>
<li>Life Assurance</li>
<li>SmartHealth - Access to private GP, Psychologist, Nutritionist along with tailored fitness plans for both you and your family</li>
<li>Benefit from personalized 1:1 career coaching with our in-house Occupational Psychologist</li>
<li>Award winning L&D platform with personal allocated training budgets</li>
<li>Enhanced paid family leave</li>
<li>Pension - 5% employee, 3% employer</li>
<li>Flexible hybrid working environment</li>
<li>Free Barista Coffee/Tea, biscuits with fruit in the WeWork office</li>
<li>Free access to WeWork discounts and free online well-being sessions</li>
<li>Vitality Health - a range of options available on this below</li>
</ul>
The Vitality Programme includes a number of reward benefits that all employees have access to as part of the plan, for example:
 <ul>
<li>Private Health cover including Dental, Optical, and Audiology</li>
<li>50% off monthly gym memberships</li>
<li>Apple watches significantly discounted based member vitality status</li>
<li>Half price trainers with Runners Need</li>
<li>Weekly rewards – Free coffee with Café Nero</li>
<li>Monthly rewards – Free Cinema ticket</li>
<li>Discounts on travel with Expedia (hotels) and Mr & Mrs Smith with discounts getting greater throughout the year based on a members vitality status</li>
<li>Amazon prime free months based on activity</li>
<li>Up to 25% cashback at Waitrose when buying healthy foods</li>
<li>75% off stays at Champneys Health Spas</li>
<li>Allen Carr’s £299 no smoking programme for free</li>
<li>Access to Vitality Healthy Mind with 30% off Headspace subscriptions and the ability to earn Vitality points for using Buddhify, Calm and Headspace</li>
<li>Discounts on Weight Watchers</li>
<li>50%-80% off Comprehensive Private Health screenings</li>
</ul>
Our Culture & Recruitment Process
 At iProov, we're incredibly proud of the culture we've carefully curated. Our culture enables diverse thought, curiosity and innovation. Our team strives to do everything to the highest standard possible to achieve the remarkable. To do that we need different perspectives, experiences and ideas alongside an environment where these are welcomed - we want everyone to feel confident in bringing their full capabilities to work. We firmly believe psychological safety is key to building and nurturing great teams. We’re a small and dynamic company, that means having the right skills is important, and we know that our best work emerges when people feel secure, welcomed and respected.
 As an equal opportunities employer, we encourage applications from people of all backgrounds. We’re committed to building a workforce that is representative of the people we serve. We will not put someone at a disadvantage or treat them less favourably because of race, color, national origin, ancestry, age, disability, creed, religion or belief, sex, sexual orientation, gender reassignment, marriage or civil partnership, or pregnancy and maternity. Our goal is to find people who are passionate about creating a safer, more secure world.
 Our recruitment process is designed to be fair and transparent, focusing solely on your qualifications, competence, and suitability for the role. We review all applications carefully and will be in touch with shortlisted candidates regarding the next steps in our interview process. If you need an adjustment for a disability or any other reason during the hiring process, please send a request to careers@iproov.com

ML Engineer (CoreAI)

Capital One

<div>White Collar Factory (95009), United Kingdom, London, London
Data Scientist / Deep Learning Practitioner
Job Title: Data Scientist / Deep Learning Practitioner - Senior Associate/Associate level 
Location: London or Nottingham
Working Pattern: 3 days in-office (Tuesday-Thursday) and 2 days remote.
Our Mission
We&rsquo;re on a mission to be a force for good in lending. Throughout our almost 30-year history, we&rsquo;ve consistently been recognised as a great place to work; in 2026, Capital One was officially ranked 9th in the UK&rsquo;s Best Workplaces&trade; list. Hear from our team about what it&rsquo;s like working at Capital One UK.
About the Role
Our Data Science team focuses on the development of Machine Learning and Deep Learning solutions, to solve business problems and deliver actionable insights. We are a talented, collaborative and enthusiastic group, who use our expertise to derive insights from complex data, working in close collaboration with our business partners. 
This role will primarily focus on developing proprietary deep learning models to address critical business challenges in underwriting. The role will also involve supporting our business partners as they develop advanced servicing products using Large Language Models.
What you&rsquo;ll do<ul><li>
Develop new deep learning approaches to advance our current underwriting models, which form the heart of our lending business.</li><li>
Apply these to new types of (multi-modal) data in order to stay at the forefront of innovation.</li><li>
Provide consultancy to our tech and product partners, to help design, develop and launch products powered by Large Language Models (LLMs). This collaboration will help provide seamless experiences for our customers and associates.</li><li>
Use a combination of business acumen, coding and statistical skills to navigate large amounts of data and extract actionable solutions.</li><li>
Work cross-functionally on projects that support key business initiatives and drive sustainable growth.</li></ul>
The skills and experience you'll need<ul><li>
Experience developing and deploying deep learning models, particularly for sequential data (e.g. time series, language) using techniques such as LSTMs or transformers.</li><li>
Hands-on experience with modern Machine/Deep Learning frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.</li><li>
Familiarity with both pre-training and fine-tuning of large-scale models</li><li>
Experience working with structured and unstructured data, such as text, logs, or time series and tokenisation techniques.</li><li>
A strong understanding of probability, statistics, machine learning and familiarity with large data set manipulation.</li><li>
Experience in producing reliable and maintainable code in Python, with an ability to adapt to new languages and technologies.</li><li>
Ability to communicate findings to a diverse business focused audience, influencing others in both verbal and written form.</li><li>
A drive for continued learning through an internal and external focus, in order to develop enterprise and industry leading solutions.</li></ul>
Where and how you'll work
This is a permanent position based in our Nottingham OR London office.
We embrace a hybrid approach to work. You'll spend three days a week in the office (Tuesday-Thursday), with Monday and Friday being dedicated work-from-home days.
Our offices are designed to inspire and support you. At our Nottingham head office, you'll find an on-site gym, restaurant and dedicated Learning Loft. Our London office boasts a rooftop running track and coffee bar.
What&rsquo;s in it for you
We invest in the growth of our people alongside our business. You will have extensive opportunities to learn and develop your career, including access to up to &pound;5,000 in funding for external qualifications.
In addition to career development, our comprehensive benefits package is designed to grow with you, ensuring your wellbeing is prioritised at every stage of your career:<ul><li>
Wealth &amp; Future: Competitive pension and performance-based bonus schemes</li><li>
Holidays: Start with 25 days of annual leave, increasing with tenure. Need more? You have the option to buy 5 additional days.</li><li>
Health: Access premium care through our private medical insurance.</li><li>
Family Support: We champion your milestones with enhanced parental leave.</li></ul>
A full list of our benefits is available here.
What you should know about how we recruit
We pride ourselves on hiring the best people, not the same people. Building diverse and inclusive teams is the right thing to do and the smart thing to do. We want to work with top talent: whoever you are, whatever you look like, wherever you come from. We know it&rsquo;s about what you do, not just what you say. That&rsquo;s why we make our recruitment process fair and accessible.
We value diversity, inclusion and belonging at our core. We empower our associates to do great work by creating an inclusive culture&mdash;one that values diverse perspectives, fosters collaboration and encourages innovative ideas&mdash;and a place where associates of all backgrounds can thrive by bringing their most authentic selves to work. We call this our Culture of Belonging, and it rests at the heart of our business.
Our associate-led Business Resource Groups were created to help support our diverse population and include over 10 groups across our offices. Because each Business Resource Group is as unique as the population it serves, they offer a range of activities, networking opportunities, special events and learning programmes to associates.
Capital One is committed to diversity in the workplace.
If you require a reasonable adjustment, please contact ukrecruitment@capitalone.com All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment.<div><div><div><div>
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div></div></div></div> 
Who We Are 
 
At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding. 
 
Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.</div>

Data Scientist / Deep Learning Practitioner

Haystack

<div>
 We are working with a pioneering technology firm that is at the forefront of developing cutting-edge AI solutions for real-world applications across various industries. This company is renowned for its innovative approach to machine learning and its commitment to pushing the boundaries of what's possible.
 
 
 The Role
 
 
 <ul>
 <li>
 Develop, train, and optimise advanced computer vision and machine learning systems
 </li>
 <li>
 Deploy machine learning solutions in constrained edge environments
 </li>
 <li>
 Work with a team of experts on innovative AI projects
 </li>
 <li>
 Contribute to the full lifecycle of machine learning model development
 
 
 </li>
 </ul>
 What You'll Need
 
 
 <ul>
 <li>
 Proven experience as a Machine Learning Engineer
 </li>
 <li>
 Expertise in computer vision and machine learning model development
 </li>
 <li>
 Familiarity with deploying models in edge environments
 </li>
 <li>
 Strong problem-solving skills and an analytical mindset
 </li>
 <li>
 Excellent communication and collaboration abilities
 
 
 </li>
 </ul>
 What's On Offer
 
 
 <ul>
 <li>
 Competitive salary based on experience
 </li>
 <li>
 Opportunity to work on groundbreaking AI technology
 </li>
 <li>
 Diverse and inclusive work environment
 </li>
 <li>
 Professional growth and development opportunities
 
 
 </li>
 </ul>
 Apply via Haystack today!
 
 
</div>

Machine Learning Engineer

<div>As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with leading researchers, hardware experts, and software engineers to build robust solutions that maximize the potential of GPU acceleration, distributed computing, and the latest open-source tools. Your work will influence our trading strategies by accelerating experimentation cycles that foster continuous innovation and refinement.

This is a unique opportunity to solve problems at the intersection of advanced machine learning and trading, where your contributions will shape the future of IMC's technology and trading capabilities.

Your Core Responsibilities:
<ul>
<li>The opportunity to be in a brand new position in a growing team</li>
<li>Develop large-scale distributed training pipelines to manage datasets and complex models</li>
<li>Build and optimize low-latency inference pipelines, ensuring models deliver real-time predictions in production systems</li>
<li>Develop libraries to improve the performance of machine learning frameworks</li>
<li>Maximize performance in training and inference using GPU hardware and acceleration libraries</li>
<li>Design scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictions</li>
<li>Collaborate with quantitative researchers to automate ML experiments, hyperparameter tuning, and model retraining</li>
<li>Partner with HPC specialists to optimize workflows, improve training speed, and reduce costs</li>
<li>Evaluate and roll out third-party tools to enhance model development, training, and inference capabilities</li>
<li>Dig into the internals of open-source ML tools to extend their capabilities and improve performance</li>
</ul>
Your Skills and Experience:
<ul>
<li>5+ years of experience in machine learning with a focus on training or inference systems</li>
<li>Hands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plus</li>
<li>Strong engineering skills, including Python, CUDA, or C++</li>
<li>Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX</li>
<li>Proficiency in GPU programming for training and inference acceleration (e.g., CuDNN, TensorRT)</li>
<li>Experience with distributed training for scaling ML workloads (e.g., Horovod, NCCL)</li>
<li>Exposure to cloud platforms and orchestration tools</li>
<li>A track record of contributing to open-source projects in machine learning, data science, or distributed systems is a plus</li></ul><div> 
About Us

IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we've been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.</div></div>

Hiscox

<div>
 
 Job Type
 
 
 
 Permanent
 
 
 
 Build a brilliant future with Hiscox
 
 
 
 
 Principal Machine Learning Engineer
 
 
 
 
 Location:
 
 London/York
 
 
 
 Why Hiscox London Market
 
 
 
 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.
 
 
 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.
 
 
 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.
 
 
 
 Role Purpose
 
 
 
 As a
 
 Principal Machine Learning Engineer (MLE)
 
 , 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.
 
 
 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.
 
 
 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.
 
 
 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.
 
 
 
 Key Responsibilities
 
 
 
 
 Technical Leadership &amp; Ownership (Individual Contributor)
 
 
 
 <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.
 
 
 
 </li>
 </ul>
 
 ML Platform Strategy &amp; Build‑Out
 
 
 
 <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.
 
 
 </li>
 </ul>
 
 Governance, Reliability &amp; Commercial Impact
 
 
 
 <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.
 
 
 
 </li>
 </ul>
 
 Collaboration &amp; Influence
 
 
 
 <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.
 
 
 
 </li>
 </ul>
 
 Technical Mentorship &amp; Capability Development
 
 
 
 <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.
 
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Bring
 
 
 
 
 Experience &amp; Background
 
 
 
 <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).
 
 
 
 </li>
 </ul>
 
 Technical Expertise
 
 
 
 <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.
 
 
 </li>
 </ul>
 
 Why Join Us?
 
 
 
 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.
 
 
 
 Work with amazing people and be part of a unique culture
 
</div>

Principal Machine Learning Engineer

Information Tech Consultants

<div>
 
 
 Job Title:
 
 Data Scientist/Machine Learning Engineer
 
 
 
 Location:
 
 UK
 
 
 
 Experience:
 
 2&ndash;5 years
 
 
 
 Education:
 
 Master's in Science (IT/Computer Science/Engineer)
 
 
 
 Employment Type:
 
 Full-Time
 
 
 
 UK based candidates only.
 
 
 
 Information Tech Consultants Ltd (ITC) is an IT management and consulting firm based in Central London. Information Tech Consultants Ltd (ITC) is an IT management and consulting firm based in Central London. We are responsible for sourcing and hiring field experts for various companies. We primarily work with Software and Cloud Hosted Services organizations as well as Mobile Apps and Service companies.
 
 
 
 Required Skills:
 
 
 <ul>
 <li>
 2-4 years of experience in Data science/Machine learning models from coding to deployment.
 </li>
 <li>
 Work with datasets using Python or R, SQL, No SQL.
 </li>
 <li>
 Assist in developing predictive and statistical models
 </li>
 <li>
 Write and optimize queries using SQL.
 </li>
 <li>
 Familiarity with data manipulation libraries (Pandas, NumPy), Understanding of statistics and probability.
 </li>
 <li>
 Hands-on experience with ML libraries like Scikit-learn, TensorFlow, or PyTorch.
 </li>
 </ul>
 
 
 Preferred Skills:
 
 
 <ul>
 <li>
 Hands on experience in coding (mandatory python and SQL or C++).
 </li>
 <li>
 Understanding of Generative AI, Computer Vision cloud technology, NLP, Deep Learning.
 </li>
 <li>
 Familiarity working with large data sets.
 </li>
 <li>
 Project Management background preferred.
 </li>
 </ul>
 
 
 
 
 
 Qualifications :
 
 
 <ul>
 <li>
 
 Master&rsquo;s (Required)
 
 in Data Science, Mathematics, Statistics, Economics, IT related fields and 2- 4 years of experience in Information Technology.
 </li>
 <li>
 You should be entitled to work in the UK with legal work authorization status.
 </li>
 <li>
 Must be willing to travel within the UK as per project/client requirements.
 </li>
 <li>
 Excellent communication skills and teamwork skills.
 </li>
 </ul>
 
 
</div>

Explore 240+ Deep learning engineer in London this July. Find roles across top companies and apply now to boost your career.

240 deep learning engineer jobs In London

AI/ML Computational Science Manager

ML Engineer (CoreAI)

Data Scientist / Deep Learning Practitioner

Machine Learning Engineer

Machine Learning Engineer

Principal Machine Learning Engineer

Machine Learning Engineer