ai systems engineer

Compare the Market

<div>
 
 Job Description
 
 
 
 
 Machine Learning Engineer
 
 
 
 
 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 Machine Learning Engineer, you will play an important role in making those systems production-ready. That means contributing to 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 where you will grow your technical skills across a fast-moving and expanding set of AI capabilities and systems. You will work closely with data scientists, engineers, and product teams - delivering well-scoped ML and AI features, contributing to engineering standards, and building your understanding of what good looks like in a modern ML engineering function.
 
 
 
 Some Of The Great Things You'll Be Doing
 
 
 
 
 ML Engineering and AI Systems
 
 
 
 <ul>
 <li>
 Deliver well-scoped ML and AI system components end-to-end, from design through to testing, deployment, and production support
 </li>
 <li>
 Contribute hands-on code to model packaging, deployment, and lifecycle automation
 </li>
 <li>
 Build and improve systems that monitor model performance, drift, reliability, and operational health
 </li>
 <li>
 Support both batch and real-time ML workloads depending on use case requirements
 </li>
 <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>
 </ul>
 
 Platform and Standards
 
 
 
 <ul>
 <li>
 Contribute to the evolution of our internal ML and AI platform to support experimentation, governance, and collaboration
 </li>
 <li>
 Apply and help promote best practices for ML and AI system design, including reproducibility, testing, CI/CD, model and agent observability and evaluation
 </li>
 <li>
 Contribute to shared tools and libraries that accelerate safe, efficient, and scalable ML development
 
 
 </li>
 </ul>
 
 Collaboration
 
 
 
 <ul>
 <li>
 Work closely with data scientists to help productionise experimental models and turn prototypes into robust services
 </li>
 <li>
 Contribute to code reviews, providing and receiving constructive feedback
 </li>
 <li>
 Participate in architecture and design discussions, raising considerations around scalability, reliability, and system interactions
 
 
 </li>
 </ul>
 
 Culture and Innovation
 
 
 
 <ul>
 <li>
 Contribute to a culture of engineering excellence, collaboration, and continuous learning
 </li>
 <li>
 Stay curious about emerging tools and approaches in MLOps and applied AI, and bring ideas for improvement to the team
 </li>
 <li>
 Support responsible AI practices, contributing to explainability, auditability, and fairness in ML systems
 
 
 </li>
 </ul>
 
 The Essentials
 
 
 
 
 What we'd like to see from you:
 
 
 
 <ul>
 <li>
 Some experience delivering ML or AI components in a production or near-production environment
 </li>
 <li>
 Solid software engineering skills in Python, with an understanding of how to write maintainable, testable code
 </li>
 <li>
 Familiarity with ML tooling and platforms such as Databricks, MLflow, Airflow, or equivalent
 </li>
 <li>
 Familiarity with CI/CD pipelines and how they apply to ML systems
 </li>
 <li>
 An understanding of ML lifecycle challenges - versioning, testing, monitoring, governance
 </li>
 <li>
 Good collaboration and communication skills, with an ability to work effectively across data science, engineering, and product teams
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Exposure to LLM-based systems - for example prompt engineering, RAG, or orchestration frameworks such as LangGraph or LangChain
 </li>
 <li>
 Familiarity with multi-step AI patterns - systems where models plan, retrieve information, and take sequences of actions
 </li>
 <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 or interest in financial services, insurance, or another regulated sector
 </li>
 <li>
 Interest in responsible AI and ML model governance
 
 
 </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>

Machine Learning Engineer

Accenture

<div><h2 class="jobSectionHeader">Description</h2>
You build the systems that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent system in production, you have owned the eval harness, and you know what happens when your agent fails at 2am because you have lived it.
As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI systems across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements.
This sits at the heart of the AI engineering talent market, demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme.<h2 class="jobSectionHeader">
Key Responsibilities</h2><ul><li>
Design and build production-grade agentic systems end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability</li><li>
Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets</li><li>
Integrate and abstract across multiple LLM providers &mdash; OpenAI, Anthropic, Vertex AI, and open-source models &mdash; with fallback routing, token, cost, and latency management</li><li>
Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring</li><li>
Embed directly with client engineering teams to design, prototype, and deploy agentic solutions &mdash; workshops, proofs of concept, code-with sessions, and architecture walkthroughs</li><li>
Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster</li><li>
Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms</li></ul></div>
 
<div><h2 class="jobSectionHeader">Basic Qualifications</h2><ul><li>
5+ years of software engineering experience in production environments</li><li>
Minimum 1 year of hands-on experience designing and deploying agentic AI solutions in a production environment &mdash; non-negotiable</li><li>
Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent &mdash; at production depth, not tutorial level</li><li>
Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs</li><li>
RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering</li><li>
LLMOps fundamentals: eval harness design, prompt versioning, and production observability</li><li>
Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm)</li><li>
Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience</li><li>
Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure</li></ul></div>

AI Native SW Engineering Specialist

Percepta

<div>
 
 Who We Are
 
 
 
 Percepta&rsquo;s mission is to
 
 transform critical institutions with applied AI.
 
 We care that industries that power the world (e.g. healthcare, manufacturing, energy) benefit from frontier technology.
 
 
 To make that happen, we embed with industry-leading customers to drive AI transformation. We bring together:
 
 
 <ul>
 <li>
 Forward-deployed expertise in engineering, product, and research
 </li>
 <li>
 Mosaic, our in-house toolkit for rapidly deploying agentic workflows
 </li>
 <li>
 Strategic partnerships with Anthropic, McKinsey, AWS, companies within the General Catalyst portfolio, and more
 
 
 </li>
 </ul>
 Our team is a quickly growing group of Applied AI Engineers, Embedded Product Managers and Researchers motivated by diffusing the promise of AI into improvements we can feel in our day to day lives.
 
 
 Percepta is a direct partnership with General Catalyst, a global transformation and investment company.
 
 
 
 About The Role
 
 
 
 We&rsquo;re hiring
 
 Applied AI Engineers
 
 who will work directly with customer executives, operators, and technical teams to define and deliver high-impact AI systems. We are excited to build out our European presence, and you will be on the front lines of helping to define our strategy and success in the region. We don't build prototypes or laboratory projects- you&rsquo;ll design, build, and ship production-grade AI agents and workflows that drive millions in business value for customers.
 
 
 
 Our Applied AI Engineers
 
 
 
 <ul>
 <li>
 Shape the AI vision: Collaborate with customer stakeholders to define their long-term AI strategy and transformation roadmap.
 </li>
 <li>
 Identify high-leverage use cases: Work backwards from the long-term vision to surface and prioritize specific AI applications that connect our ambition to measurable business value.
 </li>
 <li>
 Ship real products: Rapidly build and deploy AI solutions that work in the wild, with real users and real data.
 </li>
 <li>
 Advance our core product: Encode the lessons from our customer engagements in our Mosaic product, consistently contributing new features, patterns, and abstractions.
 
 
 </li>
 </ul>
 
 What We&rsquo;re Looking For
 
 
 
 <ul>
 <li>
 AI-nativeness: You're excited about the potential for AI to transform businesses and want to play a hands-on role in bringing frontier technology into critical institutions.
 </li>
 <li>
 Being generative and collaborative: You love constantly jamming on new &ldquo;what if&rdquo; ideas with teammates and partners.
 </li>
 <li>
 Extreme ownership: You&rsquo;re willing to jump in and love being the one on the hook. You aren&rsquo;t going to wait to be pointed at a task&mdash;you&rsquo;re going to identify what you think we should do next, and then do it.
 </li>
 <li>
 Execution excellence and speed: You can build stuff in messy environments and know how to get code written and shipped quickly. You can hold the balance of speed and quality and know when to push the pace vs. when to slow down.
 </li>
 <li>
 Customer-obsession and respect: You&rsquo;re motivated by understanding customer pain points and iterating directly with end users to deliver wins quickly.
 
 
 </li>
 </ul>
 
 Bonus if you have
 
 
 
 <ul>
 <li>
 Hands-on experience with LLM tooling (LangGraph, Mastra, Agents SDK, etc).
 </li>
 <li>
 Built and deployed production LLM-powered systems (tool use, RAG pipelines, multi-step agents, human-in-the-loop, etc).
 </li>
 <li>
 Strong technical foundations in Python/TypeScript, cloud deployment (AWS/GCP/Azure) and DevOps tooling.
 </li>
 <li>
 Prior startup or founding engineer experience, balancing craft, ownership, and speed.
 
 
 </li>
 </ul>
 We&rsquo;re working against an incredibly ambitious mission. It won&rsquo;t be easy, but it will likely be the most fulfilling work of your career. If this excites you, let's chat, even if you don't meet all of the qualifications above.
 
 
 
 Our Values
 
 
 
 
 Dream bigger:
 
 We have the unique privilege of taking on the most ambitious problems and we should chase them with optimism, responsibility, and genuine belief that we can make it happen. We have to embrace the hard things when no one else will.
 
 
 
 Heart in the game:
 
 What we're doing matters and we have to give a shit. Internally, that means fixing badness when you find it. Externally, it means honoring the trust our customers place in us with their most important problems. This isn&rsquo;t a 9-5, nor is it a job we&rsquo;re ever going to monitor your hours. We promise to put work in front of you that matters and in return, we ask you to promise to care.
 
 
 
 Win for the customer:
 
 Everyone is an engineer and the job of an engineer is to deliver outcomes, not outputs. Everything we do&mdash;the products we build, the partnerships we launch, the strategy we set&mdash;exists to make our customers successful. Delivery is the strategy.
 
 
 
 Make the call:
 
 Organizations are only as strong as the pace at which they make decisions. Everyone at Percepta should feel empowered to commit and shape the ambiguity in front of them. But "make the call" cuts both ways: make the decision
 
 and
 
 make the phone call. High-agency decision-making only works with high-bandwidth communication and we commit to never operate in silos.
 
 
 
 Intensity with kindness:
 
 We believe in excellence in execution, candor in feedback, ruthlessness in prioritization, and survivalist urgency. We also believe you don't need to be an asshole to deliver on any of this. The trust built through shared kindness and vulnerability is what makes the intensity sustainable.
</div>

Applied AI Engineer - Europe

<div><div><div>Job ID: R0057440</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 don&rsquo;t just believe in better. 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, Sky Stream 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. 
 
Role/Team overview
We are seeking an AI Operations Engineer to join our Group AI Engineering team and play a key role in keeping our autonomous AI systems running reliably across Sky. You&rsquo;ll work with cutting-edge AI technologies, from large language models to multi-agent architectures, ensuring the agentic solutions already in production stay secure, performant, observable, and cost-effective.
This is a hands-on engineering role within a forward-thinking team driving AI adoption at enterprise scale. Where the build teams take solutions from prototype to launch, you&rsquo;ll own what happens next: maintaining live agentic systems, acting as the frontline support and point of contact for the stakeholders who depend on them, and continuously improving the reliability, security, and efficiency of the platform in production.
What you&rsquo;ll do
<ul><li>Keep existing agentic and multiagent AI solutions reliable, secure, and performant in production as usage and requirements evolve.
</li></ul><ul><li>Act as the point of contact for AI system issues, triaging, diagnosing, and resolving incidents while keeping stakeholders informed throughout.
</li></ul><ul><li>Own monitoring, observability, and quality across the AI estate, going beyond uptime to track health signals specific to agents, such as output quality, model and prompt regressions, and guardrail or tool call failures.
</li></ul><ul><li>Drive FinOps for AI workloads by tracking, attributing, and optimising the cost of LLM usage, compute, and cloud infrastructure to keep solutions efficient at scale.
</li></ul><ul><li>Manage and improve the underlying infrastructure across a stack including Python, AWS, Postgres, and Cloud Foundry and/or Kubernetes, applying sound operational and DevOps practices.
</li></ul><ul><li>Identify and remediate security vulnerabilities across the AI estate, patching dependencies and resolving scan findings so systems stay compliant with Sky's security standards and agentic AI governance.
</li></ul><ul><li>Support and maintain low code automation built in Copilot Studio and Power Automate, ensuring these flows stay reliable, governed, and integrated cleanly with the wider AI platform.
</li></ul><ul><li>As this is a production operations role, on-call cover may be required in the future to keep critical AI systems running reliably outside core hours.
</li></ul>Essential criteria:
<ul><li>Solid software engineering experience in Python, with a good understanding of Agile delivery in large scale enterprise environments.
</li></ul><ul><li>Experience supporting or operating production systems, ideally AI driven or data intensive, with strong monitoring, observability, and distributed systems diagnosis skills.
</li></ul><ul><li>Practical experience with cloud (particularly AWS), relational databases such as Postgres, and familiarity with container orchestration or PaaS such as Kubernetes and Cloud Foundry.
</li></ul><ul><li>Direct experience with low code automation in Copilot Studio and Power Automate, including configuring, troubleshooting, and supporting flows and their integrations.
</li></ul><ul><li>Strong communication and stakeholder management skills, comfortable being the calm point of contact during incidents and translating technical issues for business audiences.
</li></ul><ul><li>Practical experience keeping systems secure, managing dependencies, remediating vulnerabilities, and working to enterprise security standards.
</li></ul>Desirable skills and experience:
<ul><li>Exposure to LLM or agentic AI systems, FinOps cost management, or AI governance and responsible AI controls. 
</li></ul>Benefits and perks
There's one thing people can't stop talking about when it comes to life at Sky: the perks. Here&rsquo;s a taster:
<ul><li>Free Sky TV or NOW package, including Sky Sports and Sky Cinema
</li></ul><ul><li>Pension package with up to 9% employer contribution
</li></ul><ul><li>Private healthcare with mental health support
</li></ul><ul><li>Aviva Digital GP and dental insurance
</li></ul><ul><li>Discounts on Sky products, including Sky Mobile, Sky Broadband, Sky Glass and Sky Protect
</li></ul><ul><li>Sharesave and Tech schemes
</li></ul><ul><li>A range of Sky VIP rewards and experiences 
</li></ul>How you&rsquo;ll work
We've adopted a hybrid working approach to give more flexibility on where and how we work. The hybrid working expectations for this role are 2 days in the office per week. The role is available in our Osterley or Livingston office.
Your office base
Osterley
 Our Sky Group HQ. Equipped with state-of-the-art technology and workspaces, there&rsquo;s plenty of space to see your big ideas come to life. Here you&rsquo;ll find 13 subsidised restaurants and cafes. You can re-energise at our gym, catch the latest films at our cinema, get your car washed and even get pampered at our beauty salon. 
Our Osterley Campus is just a 10-minute walk from Syon Lane train station, or you can get one of our free shuttle buses from Osterley, Gunnersbury and Ealing Broadway stations. Plus, there&rsquo;s free onsite parking available for cars, motorbikes and bicycles.
Livingston Watermark
Sky Watermark is our central site for Livingston, sitting between Glasgow and Edinburgh. With vibrant office spaces, chill-out areas, and an onsite canteen, it&rsquo;s a great place to work and connect. 
The nearest train station is Livingston North. A Sky shuttle bus runs between the station and campus every 20 minutes throughout the day. Plus, there&rsquo;s onsite parking available for cars, motorbikes and bicycles.
Who we are
We&rsquo;re Sky, a leading media and entertainment company who connect millions with entertainment, sports, news and arts through innovative products and services. Working with us means you&rsquo;ll be bringing the joy of a better experience to more people, every day. All so we can do better and deliver better for our customers, colleagues and society. 
We&rsquo;re an equal opportunity employer and value diversity at our company. We're a Disability Confident Accredited 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 as early as you can. 
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. 
To be eligible for this role you are required to have the appropriate right to work in the UK. Please be aware Sky does not offer sponsorship for this position. 
To find out more about working with us, search #LifeAtSky on social media.</div></div></div>

AI Operations Engineer (Python)

Marks & Spencer

Senior Software Engineer - Recommendation Experiences

Quantum

<div>Our Company 
At Quantum, we connect global brands with high-intent consumers. We turn intent into action and complexity into clarity.
Our Mission is clear, to help smarter, faster buying decisions. Our vision, to be the world&rsquo;s most used digital comparison service, delivering value and simplicity to millions.
We drive growth through data-driven affiliate marketing built for performance from day one. Every campaign is measurable, optimised in real time, and designed to scale.
With in-house tech, full-stack analytics, and a compliance-first mindset, we give our partners an edge. We drive confident decisions and growth in regulated and high-growth sectors. We&rsquo;ve helped ambitious brands grow faster, smarter, and globally.
The Role 
We're looking for an experienced Senior AI Engineer to join our team. 
You'll be at the forefront of designing, developing, and deploying AI systems that power personalised advertising, customer journey analytics, audience segmentation, and real-time bidding strategies.
Working closely with BI, data engineers, and product teams, you'll help build scalable AI solutions that deliver measurable business outcomes for some of the world's most recognised brands. Our infrastructure is powered by Google Cloud Platform (GCP), and we take pride in applying cutting-edge AI techniques to real-world marketing and advertising challenges. 
Key Responsibilities<ul><li>
Architecture &amp; Multi-Agent Design: Design, build, and deploy scalable multi-agent systems and generative AI features for Mar Tech challenges including ad targeting, user segmentation, and content personalisation.</li><li>
Advanced Agentic Workflows: Research and implement agentic design patterns such as planning, reflection, and tool usage using orchestration frameworks like LangGraph, AutoGen, or CrewAI.</li><li>
Cross-Functional Collaboration: Work closely across the organisation to translate ambiguous business objectives into discrete agent personas, tool definitions, and behavioural boundaries.</li><li>
Performance &amp; Guardrails: Monitor and optimise multi-agent systems in production, tracking agent-specific metrics including token efficiency, execution loops, and tool-calling accuracy to ensure system reliability.</li><li>
Security &amp; Compliance: Maintain high standards for data security, model explainability, and mitigation of agent-specific risks such as prompt injection and unintended tool execution in compliance with GDPR and CCPA.</li><li>
Mentorship &amp; Best Practices: Support and develop junior engineers and help champion best practices in agent-oriented programming, prompt engineering, model evaluation, and scalable cloud infrastructure.</li></ul>
About You<ul><li>
Experienced in software engineering, ideally in Ad Tech, Mar Tech, or similarly complex and high-scale environments</li><li>
Experience building multi-agent or single-agent architecture with integrations to APIs and/or MCPs</li><li>
A good understanding of supervised, unsupervised, and reinforcement learning methods alongside experience working with foundation models and prompt engineering</li><li>
Practical experience with GCP services or AWS equivalent such as Vertex AI, BigQuery ML, Dataflow, AI Platform Pipelines, and Dataproc</li><li>
Practical experience with CI/CD for AI/ML, model versioning, monitoring, and AI Ops practices</li><li>
An understanding of marketing and advertising concepts such as customer lifetime value, attribution modelling, real-time bidding, and audience targeting is a plus</li><li>
Familiarity with data pipeline orchestration tools such as Apache Airflow and Kubernetes is a plus</li><li>
You do your best work as part of a team and enjoy sharing knowledge just as much as gaining it</li><li>
Confident navigating ambiguity and a fast moving environment</li><li>
Excellent written and verbal communication skills</li><li>
Collaborative and grounded, you value the perspectives of others and create space for everyone to contribute</li></ul>
What You&rsquo;ll Get<ul><li>
Private Health Care (Bupa)</li><li>
Hybrid Working (3 days in office)</li><li>
Travel Insurance</li><li>
Competitive Base Salary</li><li>
Company Bonus Scheme</li><li>
Paid for AI Subscription (Claude / ChatGPT / Gemini)</li><li>
Market-Leading Training Programme</li><li>
Recognition &amp; Reward Scheme</li><li>
Annual Company Conference
</li><li>Regular Happy Hours &amp; Team Lunches</li><li>
Free Coffee, Drinks &amp; Snacks</li></ul>
What&rsquo;s the next step? 
 
Our hiring process ensures we're recruiting the right people for the role. We ensure that people are as suitable for us as we are for them. 
 
If you like the sound of what we're all about at Quantum and want to join a team where you can make an impact, please apply or contact us at careers@quantum.media.</div>

Senior AI Engineer

Ventula Consulting

<div>
 
 
 AI / ML Engineer - AI Startup - London - &pound;80k - &pound;120k
 
 
 
 
 
 
 A newly established Voice AI startup with multi-million funding, is looking to hire an AI / ML Engineer to focus on their ML pipelines which process very high-volume events at scale.
 
 
 
 
 
 Our client is looking for an individual with significant experience as either an AI Engineer or Machine Learning Engineer with clear evidence of shipping LLM powered ML products
 
 
 
 
 
 To be suitable for this role you will require the below:
 
 
 
 
 
 
 Key Requirements
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Machine Learning, or a related field
 </li>
 <li>
 Excellent experience as a, ML, or AI Engineer, with evidence of shipping production systems
 </li>
 <li>
 Strong Python skills and experience with FastAPI
 </li>
 <li>
 Experience working modern MLOps tools, ideally Kubeflow
 </li>
 <li>
 Strong experience working closely with LLMs (including fine-tuning, RAG, prompt engineering)
 </li>
 <li>
 Strong problem-solving skills and ability to communicate technical trade-offs clearly
 </li>
 <li>
 Collaborative mindset with experience working across technical and non-technical teams
 </li>
 </ul>
 
 
 
 
 
 
 
 This position is a permanent role, based in London, with 3-4 days a week in the company's office
 
 
 
 
 
 The role offers a salary between &pound;80,000 - &pound;120,000
 
</div>

AI / ML Engineer

Explore 410+ Ai systems engineer in London this July. Find roles across top companies and apply now to boost your career.