ai architect / engineer (agentic ai & llm architecture)

lead software engineer

platform engineer

senior data scientist

software engineer

ai engineer

machine learning engineer

Faculty

<div><h2 class="jobSectionHeader">Why Faculty? 
</h2> 
We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we&rsquo;ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.
We don&rsquo;t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.
Our business, and reputation, is growing fast and we&rsquo;re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.
AI is an epoch-defining technology, join a company where you&rsquo;ll be empowered to envision its most powerful applications, and to make them happen.<div> 
</div><h2 class="jobSectionHeader">
About the team</h2><div></div> 
Our Energy, Transition and Environment business unit is pioneering meaningful change in the clean energy revolution. Our vision is to accelerate the transition to net-zero emissions and drive efficiencies for a new era of utility companies.<div></div> 
We believe that the responsible, and intelligent, deployment of AI is critical to the success of this mission. We partner with a wide range of clients - from major energy operators, to GreenTech startups, and national infrastructure providers - to build solutions which return measurable impact and move us towards a smarter, cleaner, and more sustainable world.<div></div><div> 
</div><h2 class="jobSectionHeader">
About the role</h2><div></div> 
Join us as a Machine Learning Engineer to deliver bespoke, impactful AI solutions for our diverse clients.<div></div> 
You will be instrumental in bringing machine learning out of the lab and into the real world, contributing to scalable software architecture and defining best practices. Working with clients, and cross-functional teams, you'll ensure technical feasibility and timely delivery of high-quality, production-grade ML systems.<div> 
</div><div>
</div><h2 class="jobSectionHeader">What you'll be doing:</h2><div></div><ul><li> 
Building and deploying production-grade ML software, tools, and infrastructure.</li><li>
Creating reusable, scalable solutions that accelerate the delivery of ML systems.</li><li>
Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges.</li><li>
Leading technical scoping and architectural decisions to ensure project feasibility and impact.</li><li>
Defining and implementing Faculty&rsquo;s standards for deploying machine learning at scale.</li><li>
Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders.<div> 
</div></li></ul><h2 class="jobSectionHeader">
Who we're looking for:</h2><div></div><ul><li> 
You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch.</li><li>
You possess strong Python skills and solid experience in software engineering best practices.</li><li>
You bring hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security.</li><li>
You've worked with container and orchestration tools such at Docker &amp; Kubernetes to build and manage applications at scale</li><li>
You are comfortable with core ML concepts, including probability, statistics, and common learning techniques.</li><li>
You're an excellent communicator, able to guide technical teams and confidently advise non-technical stakeholders.</li><li>
You thrive in a fast-paced environment, and enjoy the autonomy to own scope, solve and delivery solutions</li></ul><div> 
</div><h2 class="jobSectionHeader">
Our Interview Process</h2><div></div><ul><li> 
Talent Team Screen (30 minutes)</li><li>
Pair Programming Interview (90 minutes)
</li><li>System Design Interview (90 minutes)
</li><li>Commercial Interview (60 minutes)</li></ul> 
#LI-PRIO<h2 class="jobSectionHeader"> 
Our Recruitment Ethos</h2>
We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We&rsquo;re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Some of our standout benefits:<ul><li>
Unlimited Annual Leave Policy</li><li>
Private healthcare and dental</li><li>
Enhanced parental leave</li><li>
Family-Friendly Flexibility &amp; Flexible working</li><li>
Sanctus Coaching</li><li>
Hybrid Working</li></ul>
If you don&rsquo;t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.</div>

Machine learning Engineer

Intact Insurance UK

<div>
 
 APPLY NOW!
 
 
 
 Intact Insurance is the new name for RSA in the UK, Ireland, and across Europe. It&rsquo;s a new name and a new way to do business. Backed by global expertise and a commitment to service that feels different, we&rsquo;re focused on making insurance simpler, faster, and more responsive.
 
 
 
 Shape The Future
 
 
 
 We&rsquo;re leading a transformation in insurance helping people, businesses and society prosper in good times and be resilient in bad times. When you join us, you&rsquo;re not just taking a job, you&rsquo;re stepping into a career where you can make a real difference.
 
 
 
 Grow With Us
 
 
 
 We&rsquo;re customer-driven, community-focused, and committed to helping our people grow. Whether you&rsquo;re early in your journey or bringing years of experience, we&rsquo;ll support you with the tools, flexibility, and opportunities to thrive.
 
 
 
 Win As a Team
 
 
 
 We&rsquo;re looking for a Machine Learning Engineer to help build and run production-ready ML systems that make a real impact across the business. You&rsquo;ll work closely with Data Scientists and engineering teams, shaping the ML roadmap, developing scalable solutions, and driving innovation while growing your career.
 
 
 
 You&rsquo;ll Make An Impact By
 
 
 
 <ul>
 <li>
 Build and automate ML pipelines for feature engineering, model training, and model scoring using Python, PySpark, Databricks, and MLflow.
 </li>
 <li>
 Productionise Data Science models, converting notebooks into modular, tested, production-ready code.
 </li>
 <li>
 Deploy models into batch and real-time environments, managing versioning, promotion, rollback, and scheduled workflows via MLflow and APIs.
 </li>
 <li>
 Implement monitoring and observability, including data and model drift detection, performance alerts, logging, and automated retraining.
 </li>
 <li>
 Collaborate with Data Engineering and Platform teams on CI/CD integration, pipeline performance, compute optimisation, and secure deployment patterns.
 </li>
 <li>
 Maintain engineering standards, ensuring high-quality testing, documentation, code quality, reproducibility, and operational reliability.
 
 
 </li>
 </ul>
 
 Your Skills And Experience
 
 
 
 <ul>
 <li>
 Experience with ML platforms including Databricks, MLflow, Delta Lake, and cloud environments.
 </li>
 <li>
 Proficient in Python, PySpark, and SQL, following production coding best practices.
 </li>
 <li>
 Understanding of data, distributed ML pipelines, and model deployment patterns, including monitoring, drift detection, and lifecycle operations.
 </li>
 <li>
 Exposure to CI/CD, containerisation, and API integration, with the ability to build scalable, production-ready ML systems.
 </li>
 <li>
 Comfortable working technically while communicating effectively with Data Scientists, stakeholders, and cross-functional teams.
 
 
 </li>
 </ul>
 
 Why You&rsquo;ll Love It Here
 
 
 
 Being part of our team means you&rsquo;ll have the support and freedom to bring your best self to work each day. As a permanent member, here&rsquo;s what you can look forward to
 
 
 <ul>
 <li>
 Annual discretionary bonus
 </li>
 <li>
 Up to 11% pension contributions
 </li>
 <li>
 Hybrid working + flexible hours
 </li>
 <li>
 25 days annual leave + bank holidays + buy/sell options
 </li>
 <li>
 Health &amp; wellbeing + virtual GP
 </li>
 <li>
 Career development and mentoring
 </li>
 <li>
 Inclusive culture + employee networks
 </li>
 <li>
 Share investment options
 
 
 </li>
 </ul>
 
 Our DEI Commitment
 
 
 
 We celebrate individuality and believe our differences make us stronger. We&rsquo;re proud to foster a culture where everyone feels respected, valued, and empowered to thrive.
 
 
 As an Equal Opportunity and Disability Confident Employer, we ensure fair consideration for all applicants and offer interviews to all disabled candidates who meet the essential criteria.
 
 
 We understand that everyone&rsquo;s circumstances are different and are happy to explore flexible working options such as reduced hours or job shares to support work&ndash;life balance.
 
 
 If you meet the core criteria but not every requirement, we&rsquo;d still love to hear from you. Let&rsquo;s explore how this role could support your next career step. If you need adjustments during the recruitment process, just let us know we&rsquo;re here to support you.
 
 
</div>

Machine Learning Engineer

Onsera Health

<div>
 
 The Challenge
 
 
 Cardiometabolic conditions will impact 80-90% of people throughout their lifetimes, representing the leading cause of death globally and an important risk factor for neurodegenerative diseases and cancer. Sustainably addressing these diseases requires breakthrough therapeutics, AI/ML innovation, and transformative business models that translate clinical outcomes into economic value.
 
 
 The Opportunity
 
 
 This is an opportunity to build the ML and AI foundations of Onsera Health's breakthrough healthcare platform. Backed by Population Health Partners (PHP)&mdash;the proven venture platform behind Metsera and Corsera Health&mdash;we're building the future of population health management.
 
 
 
 As a Senior Machine Learning Engineer, you will sit at the intersection of data science, platform engineering, and production systems.
 
 Your mission is to design and operate the foundations that allow ML, analytics, and agentic AI systems to move safely and reliably from experimentation into regulated healthcare production environments on Google Cloud Platform. You will be the primary interface between Data Science and Platform Engineering, enabling rapid iteration while enforcing production and compliance standards.
 
 
 Responsibilities
 
 <ul>
 <li>
 
 Design and implement Onsera's agentic AI platform
 
 &ndash; architect LLM/agent framework selection, standardized patterns for tools, memory, guardrails, evaluation, and observability
 </li>
 <li>
 
 Define MLOps protocols for agentic systems
 
 &ndash; environment separation, versioning of prompts, tools, and policies, cost controls, rate-limiting, and fail-safe mechanisms
 </li>
 <li>
 
 Bridge data science and platform engineering
 
 &ndash; translate experimentation needs into GCP infrastructure, scalable compute patterns, and reproducible development environments
 </li>
 <li>
 
 Productionize data science code
 
 &ndash; convert research-grade notebooks into tested, modular, production-grade Python services, batch and streaming pipelines, and scheduled workflows
 </li>
 <li>
 
 Build production-grade data pipelines
 
 &ndash; develop idempotent, observable, and cost-efficient pipelines using BigQuery, Airflow, Google Workflows, and Cloud Run
 </li>
 <li>
 
 Implement CI/CD for ML workloads
 
 &ndash; automated validation, monitoring, rollback strategies, and model lifecycle management
 </li>
 <li>
 
 Establish reliability and governance
 
 &ndash; logging, metrics, tracing, data quality checks, and auditability for model decisions, data lineage, and agent actions
 </li>
 </ul>
 
 What We Offer
 
 <ul>
 <li>
 Mission-driven work addressing critical public health and healthcare economics challenges
 </li>
 <li>
 Ground-floor opportunity to build the ML/AI infrastructure for a breakthrough healthcare platform
 </li>
 <li>
 Partnership with a world-class team of industry leaders, innovators, technologists, bioscientists, and clinicians from PHP and beyond
 </li>
 <li>
 A fast-paced, dynamic, and highly collaborative work environment
 </li>
 <li>
 Competitive salary and benefits package, including participation in our equity program
 </li>
 </ul>
 
 
 
 
 Minimum Qualifications
 
 <ul>
 <li>
 5+ years of experience in machine learning engineering, data engineering, or a related field
 </li>
 <li>
 Strong Python engineering skills with production-quality, typed, and tested code
 </li>
 <li>
 Track record productionizing ML models in batch and/or real-time environments
 </li>
 <li>
 Hands-on experience with analytical data warehouses (BigQuery or equivalent) and workflow orchestration (Airflow or similar)
 </li>
 <li>
 Experience deploying ML systems on GCP, including Cloud Run, GCS, and IAM
 </li>
 <li>
 Infrastructure-as-Code experience (Terraform or equivalent)
 </li>
 <li>
 Experience with feature engineering, model lifecycle management, and ML evaluation
 </li>
 <li>
 Demonstrated ability to collaborate across Data Science, Product, and Platform teams
 </li>
 </ul>
 
 Preferred Qualifications
 
 <ul>
 <li>
 Experience with LLMs, agent frameworks, or AI orchestration systems in production
 </li>
 <li>
 Familiarity with prompt management, tool calling, evaluation, and AI safety patterns
 </li>
 <li>
 Healthcare or regulated-industry experience, including familiarity with HIPAA or SOC-2 compliance
 </li>
 <li>
 Experience with claims data, EHR-derived datasets, or real-world evidence
 </li>
 <li>
 Strong written and verbal communication skills with technical and non-technical stakeholders
 </li>
 </ul>
 
 About Onsera Health
 
 
 We are an early-stage health AI company revolutionizing cardiometabolic care and population health economics connected to weight loss. Our unique position within the PHP ecosystem provides:
 
 <ul>
 <li>
 
 Venture track record:
 
 A proven track record of success in building biotech and healthcare companies
 </li>
 <li>
 
 Deep capital:
 
 Funding and resourcing to support deep tech and scientific R&amp;D&mdash;and to drive growth
 </li>
 <li>
 
 Strategic guidance:
 
 Direct access to industry pioneers (including founders of The Medicines Company and Metsera), healthcare experts (including leaders in virtual care, former FDA commissioners), strategists (McKinsey/QuantumBlack alumni), and world-class scientific talent
 </li>
 <li>
 
 Expert network:
 
 Established connections across pharma, payers, and providers
 </li>
 <li>
 
 Startup agility:
 
 Ownership in the venture, founder mentality, and ground-floor impact
 </li>
 </ul>
 
 About PHP
 
 
 Population Health Partners (PHP) is a premier investment firm established in 2020, aimed at transforming health outcomes for large populations. With offices in New York and London, PHP combines financial resources with industry-leading capabilities and technology. The firm's incubation portfolio includes Metsera and Corsera Health.
 
 
 
 Leadership:
 
 Led by industry veterans including Clive Meanwell (The Medicines Company), Chris Cox (The Medicines Company), and Whit Bernard (Metsera), bringing decades of founder experience and operational excellence in biopharma and healthcare, and Roy Berggren, 30+ year McKinsey Healthcare leader.
 
</div>

Senior Machine Learning Engineer

<div><div><div>Job ID: R0048311</div>
</div><div><div><div><div><div>Location</div>
<div>London, Middlesex</div>
</div></div></div><div></div><div><div><div><div>Hours/week</div>
<div>37.5 hrs/week</div>
</div></div></div><div></div><div><div><div><div>Payrate range</div>
<div>Unknown</div>
</div></div></div></div><div><div>We believe in better. And we make it happen.
Better content. Better products. And better careers.
Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate.
We turn big ideas into the products, content and services millions of people love.
And we do it all right here at Sky.
What you'll do
 
We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform.
<ul><li>Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis.</li>
<li>Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets.</li>
<li>Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance.</li>
<li>Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement.</li>
<li>Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs.</li>
<li>Research &amp; Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems.</li> 
</ul> 
What you'll bring
<ul><li>Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance.
</li><li>Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). .</li>
<li>Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe).</li>
<li>Experience with high-volume data processing and real-time streaming architectures.</li>
<li>Strong understanding of recommendation system design and personalisation algorithms.</li>
<li>Familiarity with Generative AI and its applications in production settings.</li>
<li>Exceptional communication and analytical problem-solving skills.</li>
<li>Proven successful experience in mentoring less experienced engineers to improve their technical skills</li>
</ul>A Typical Day at the Office
When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) caf&eacute;s or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you&rsquo;ll join your team and pick the first task to get cracking on.
At lunchtime, you&rsquo;ve got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup &ndash; whatever suits you. Once you&rsquo;re back, you&rsquo;ll carry on working with your team on your current feature.
Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective.
Global OTT Technology
Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world&rsquo;s best entertainment, news and sport.
The rewards
There's one thing people can't stop talking about when it comes to #LifeAtSky: the perks. Here&rsquo;s a taster:
<ul><li>Sky Q, for the TV you love all in one place</li>
<li>The magic of Sky Glass at an exclusive rate</li>
<li>A generous pension package</li>
<li>Private healthcare</li>
<li>Discounted mobile and broadband</li>
<li>A wide range of Sky VIP rewards and experiences</li>
</ul>Inclusion &amp; how you'll work
We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can.
We&rsquo;ve embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You&rsquo;ll find out more about what hybrid working looks like for your role later on in the recruitment process.
Your office space
Osterley
Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers.
On campus, you&rsquo;ll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon.
We'd love to hear from you
Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It&rsquo;s a place where you can explore what if, how far, and what next.
But better doesn&rsquo;t stop at what we do, it&rsquo;s how we do it, too. We embrace each other&rsquo;s differences. We support our community and contribute to a sustainable future for our business and the planet.
If you believe in better, we&rsquo;ll back you all the way.
Just so you know: if your application is successful, we&rsquo;ll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.</div></div></div>

Senior Machine Learning Engineer (Recommendation)

Compare The Market

<div>Senior Machine Learning Engineer &ndash; Customer AI
Function: Data &amp; AI Solutions
 
Location: Hybrid, London office 
Curious about what&rsquo;s next?
 
So are we. Join Compare the Market and help to make financial decision making a breeze for millions.
At Compare the Market, we&rsquo;re a purpose-driven business powered by tech and AI. We&rsquo;re building high-performing, results-driven teams with the skills, mindset, and ambition to deliver outcomes at pace. Every role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers.
We&rsquo;ve carved a meerkat-shaped niche and we&rsquo;re looking for ambitious, curious thinkers who thrive in a fast-moving, high-impact environment. If you love accountability, embrace challenge, and want to make a real difference, you&rsquo;ll fit right in. 
We&rsquo;d love you to be part of our journey.
Compare the Market is building AI systems that connect directly to how millions of people in the UK find and buy financial products - and as a Senior Machine Learning Engineer, you will play a central role in making those systems production-ready. That means owning the engineering that takes ML models and AI capabilities from experimentation into reliable, scalable production use: the pipelines, the deployment tooling, the monitoring, and the shared components that make the whole thing work.
This is a hands-on role with real technical scope. You will work closely with data scientists, engineers, and product teams - contributing to architecture decisions, raising engineering standards, and building the reusable tooling that raises the pace and quality of delivery across a fast-moving and expanding set of AI capabilities and systems. 
Some of the great things you'll be doing:
ML Engineering and AI Systems
<ul><li>Own the end-to-end delivery of production machine learning and AI solutions in collaboration with data scientists and product teams
</li><li>Design and build model pipelines for training, validation, and deployment using modern tooling (e.g. MLflow, Kubernetes)
</li><li>Contribute hands-on code to model packaging, deployment, and lifecycle automation
</li><li>Build systems that monitor model performance, drift, reliability and operational health in real time
</li><li>Support both batch and real-time ML workloads depending on use case requirements
</li>Work on emerging AI and LLM-powered capabilities, helping integrate modern AI techniques into production systems where they can deliver real user value 
<li>
</li></ul>Platform and Standards
<ul><li>Help evolve our internal ML and AI platform to support experimentation, governance, and collaboration
</li><li>Define and promote best practices for ML and AI system design, including reproducibility, testing, CI/CD, model and agent observability and evaluation
</li>Develop shared tools and libraries that accelerate safe, efficient, and scalable ML development 
<li>
</li></ul>Collaboration and Technical Leadership
<ul><li>Work closely with data scientists to productionise experimental models and turn prototypes into robust services
</li><li>Act as a technical mentor and code reviewer for other engineers and contributors
</li>Provide technical leadership across ML and AI initiatives, contributing to architecture discussions and design reviews 
<li>
</li></ul>Culture and Innovation
<ul><li>Contribute to a culture of engineering excellence, collaboration, and continuous learning
</li><li>Stay up to date on emerging tools and approaches in MLOps and applied AI, helping evaluate and adopt technologies where appropriate
</li>Support responsible AI practices, contributing to explainability, auditability, and fairness in ML systems 
<li>
</li></ul>What we'd like to see from you:
The Essentials
<ul><li>Hands-on experience with LLM-based systems: prompt engineering, RAG, tool use, or orchestration frameworks such as LangGraph or LangChain
</li><li>Familiarity with multi-step AI patterns - building systems where models plan, retrieve information and take sequences of actions
</li><li>Strong experience deploying ML models into production in cloud-native environments
</li><li>Solid software engineering skills in Python, with experience building scalable services, APIs, and production-quality code
</li><li>Experience with modern ML tooling and platforms (e.g. Databricks, MLflow, Airflow, Kubeflow, SageMaker, Vertex AI)
</li><li>Familiarity with CI/CD pipelines and infrastructure-as-code (e.g. Terraform, CloudFormation)
</li><li>Experience building robust, maintainable, and testable ML pipelines and APIs, including batch or real-time model delivery
</li><li>Strong understanding of ML lifecycle challenges - versioning, testing, monitoring, governance
</li>Excellent collaboration and communication skills, with experience working across data science, engineering, and product teams 
<li>
</li></ul>Nice to Have
<ul><li>Active personal use of AI-assisted or agentic coding tools, and an interest in how similar patterns could be applied to automate and accelerate ML engineering workflows - candidates who are exploring this space, even at an early stage, are encouraged to talk about it
</li><li>Experience in financial services, insurance or another regulated sector
</li><li>Experience deploying real-time or streaming ML models (e.g. Kafka, Flink, Spark Structured Streaming)
</li><li>Passion for automation, tooling, and building reusable systems
</li>Interest in responsible AI and ML model governance 
<li>
</li></ul>Why Compare the Market?
We&rsquo;re a business built for pace and performance. Here, you&rsquo;ll be encouraged to think differently, act boldly, and deliver brilliantly in a culture that values results and rewards progress.
We believe diverse teams make better decisions, and we&rsquo;re committed to creating an inclusive workplace where everyone feels empowered to grow, contribute, and thrive.
If you&rsquo;re ready to stretch yourself, raise the bar, and grow with a team that&rsquo;s serious about performance, innovation, and purpose, we&rsquo;d love to hear from you.</div>

Senior Machine Learning Engineer - Customer AI

Accenture

<div>YOU ARE
As a Senior 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 Senior Manager

Muzz

<div>
 
 
 London, UK - Hybrid (Tue, Wed &amp; Thur in Office)
 
 
 
 
 &pound;80,000 - &pound;90,000 + equity
 
 
 
 
 
 
 We&rsquo;re looking for a smart and ambitious data scientist, with real entrepreneurial flair to join our team and understand our members and all the metrics that matter. Love numbers and love being commercial? This role presents an opportunity to mold the future of the data science team, explore new ideas and new technologies.
 
 
 
 
 
 Muzz is the world&rsquo;s largest Muslim dating and marriage app. We&rsquo;ve got over 15 million members and have helped more than 800,000 couples get married. We&rsquo;re on our way to become the first $1 billion Muslim tech brand - but we need your help!
 
 
 
 
 
 
 Day to day
 
 
 <ul>
 <li>
 You'll be joining a dynamic data science team whose goal is to grow the company and optimize our products as we expand into new markets around the world
 </li>
 <li>
 You'll be understanding our user behaviour on the platform with a view to generating actionable insights in terms of both product and marketing
 </li>
 <li>
 You'll work closely with our product, engineering and growth teams
 </li>
 <li>
 You'll be a proactive self-starter, driving innovation with a product focus
 </li>
 <li>
 You&rsquo;ll be diving into a range of data to solve our highest impact and complex challenges
 </li>
 <li>
 You'll own and evolve the production ML systems behind our personalization and recommendations serving millions of users
 </li>
 <li>
 You'll use AI tools as a core part of how you work and help set how the wider team gets the most out of them
 </li>
 <li>
 You'll raise the bar for the team - mentoring analysts and data scientists, and helping shape our technical standards and roadmap
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 At least 5 years of experience in a Data Scientist or Machine Learning Engineer role
 </li>
 <li>
 Strong Python and SQL knowledge
 </li>
 <li>
 Strong grounding in the statistical methods behind personalization and recommendations models - e.g. embeddings, ranking, collaborative filtering
 </li>
 <li>
 Excellent written and verbal communication skills and presenting to non-technical audiences
 </li>
 <li>
 Commercial mindset with the ability to harness customer insights to optimise our marketing and products
 </li>
 <li>
 Ability to work collaboratively in cross-functional teams
 </li>
 <li>
 Passionate about solving complex and challenging data problems
 </li>
 <li>
 Experience in designing and conducting A/B experiments
 </li>
 <li>
 A proven track record of developing and owning production ML pipelines - including data processing, deployment, monitoring, retraining
 </li>
 <li>
 Demonstrated end-to-end ownership of significant ML projects - from framing the problem to shipping it, and through the messy realities of live performance, edge cases and iteration once real users hit it
 </li>
 </ul>
 
 
 
 
 
 Nice to have
 
 
 <ul>
 <li>
 Hands-on experience with recommender systems, with real-time or near-real-time updates and serving
 </li>
 <li>
 Experience in consumer-facing mobile-first products
 </li>
 <li>
 Experience with GCP platform - BigQuery/VertexAI
 </li>
 </ul>
 
 
 
</div>

Senior Data Scientist

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