lead software engineer

platform engineer

software engineer

machine learning engineer

senior software engineer

ai engineer

SQLI

<div>
 
 We Elevate. Digitally.
 
 
 
 
 SQLI is a European leader in digital transformation and customer experience, helping major international brands drive growth through technology. From strategy to implementation, we design and deliver high-performance architectures and engaging digital experiences by combining advanced technologies, proven methodologies, and deep technical expertise.
 
 
 
 
 With 2,200 people across 12 countries, we&rsquo;re looking for passionate individuals who share our values: Creative Spirit, Commitment, and Forward Thinking.
 
 
 
 
 
 
 Job Description
 
 
 
 
 
 
 About the role
 
 
 
 
 
 
 The AI Engineer is the build engine of our AI practice. You turn business requirements into working AI solutions, fast, using coding agents and frontier models, then take the ones that prove their worth into production with the security, compliance, and reliability that enterprise clients demand.
 
 
 
 
 This is not a model-training role. We are not building or fine-tuning models from scratch. You build agentic workflows and LLM-powered applications on top of frontier models, wire them into real enterprise systems, and make them safe to run.
 
 
 
 
 You will work as part of the delivery team alongside consultants, business analysts, and architects. The consultant carries the client relationship and the architect owns the hard architectural calls. You own the build and you make real engineering decisions, not just execute someone else&rsquo;s spec. You are proactive about spotting better ways to build, and trusted to deliver without close supervision.
 
 
 
 
 
 
 What you will do
 
 
 
 
 
 <ul>
 <li>
 
 Use coding agents to prototype AI solutions quickly against real client requirements, so the team can validate value before committing to a full build
 
 
 
 </li>
 <li>
 
 Build, deploy, and maintain LLM-powered applications and agents that align with enterprise architecture principles and standards, with evaluation, monitoring, and token tracking in place from day one
 
 
 
 </li>
 <li>
 
 Set up MCP connectors and permissions against client systems, taking real care over data handling, access control, and what an agent is and is not allowed to do
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Build production solutions that meet client security requirements and European data protection obligations, including GDPR. This is not optional and not an afterthought
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Collaborate with consultants, business analysts, and architects to break business requirements down into solutions that are feasible, maintainable, and safe
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Create reusable AI assets and accelerators for the practice, including skills, plugins, and MCP servers that make future engagements faster
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Support Data &amp; AI teams with best practices around AI-assisted development, documentation, and automation, and coach less experienced colleagues on agentic build patterns and security standards
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Document deployment, upgrade paths, and maintenance so SQLI and our clients can own what you build after handover
 
 
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 
 
 
 <ul>
 <li>
 
 Proven experience with AI-assisted development. You have shipped something real with Claude or another agent platform, not just followed tutorials
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Strong TypeScript and/or Python for agentic glue code, custom MCP work, and evaluation
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience building RAG applications
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Hands-on with creating and using agent plugins, skills, and MCP servers for repeatable agentic workflows
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Skilled at engineering the prompts and context that let agents do work as autonomously as is safe and sensible
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Solid grasp of security, access control, and data protection (including GDPR) when building systems that act against real client data with real permissions
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience setting up CI/CD pipelines and automation
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Able to take a prototype through to a production-grade build, not just one or the other
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Strong collaboration and communication skills, ideally from an agency or consulting setting
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proactive and autonomous, able to spot opportunities, make sound engineering decisions, and own delivery rather than wait to be told how to build
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Business-level English, able to understand business requirements directly from clients and communicate clearly in calls and in writing
 
 
 
 </li>
 </ul>
 
 
 
 Nice to have
 
 
 
 
 
 <ul>
 <li>
 
 Familiar with Microsoft Azure, particularly Azure AI infrastructure, as our primary cloud for production AI
 
 
 
 </li>
 <li>
 
 Hands-on with Anthropic&rsquo;s managed agent infrastructure (Claude managed agents, the agents API)
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Prior work on evaluation methods for LLM outputs
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience in e-commerce, or from an AI, agentic, or workflow automation background
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Comfortable presenting technical work and learnings to a non-engineering audience
 
 
 
 
 
 </li>
 </ul>
 
 Additional Information
 
 
 
 
 
 
 How we will work together
 
 
 
 
 
 
 You will report into the Data &amp; AI service line leadership and work as part of client delivery teams across the service line and the wider SQLI group. The role is primarily billable client work. You will occasionally join client sessions for technical depth, but the consultant carries the relationship. We are looking for someone who can own technical decisions on the build, not only execute, with room to grow toward an AI Architect track as the practice scales.
 
 
 
 
 
 
 How to apply
 
 
 
 
 
 
 Send a short note covering:
 
 
 
 <ol>
 <li>
 
 One thing you have built recently with Claude Code or a Claude-based agent, with a link if possible
 
 
 
 </li>
 </ol>
 <ol>
 <li>
 
 How you would take an agent that touches real client systems from a quick prototype to something safe to run in production
 
 
 
 </li>
 </ol>
 <ol>
 <li>
 
 Your notice period and earliest start date
 
 
 
 </li>
 </ol>
 
 
 Why you&rsquo;ll love working at SQLI?
 
 
 
 
 <ul>
 <li>
 A flexible remote working policy: 3 days per week
 </li>
 <li>
 Continuous learning opportunities and certifications to support your development
 </li>
 <li>
 Personalised support: career follow-up, diverse projects, and strong team collaboration
 </li>
 <li>
 Regular rituals: internal communications on tech and AI topics, internal events, and meet-ups
 </li>
 </ul>
</div>

AI Engineer

Houseful

<div>6 months Initial Contract - Must work from the UK
Alto Software Group (ASG) is a leading B2B SaaS platform serving the UK property industry. We power thousands of estate agency branches and support a significant proportion of UK housing transactions each year.
We are building a data-driven, operationally efficient platform business. AI will be a structural lever in improving internal productivity, reducing operational cost, and enhancing customer experience.
This is a hands-on delivery role responsible for building the automations and AI integrations that embed AI into how we operate.
The Role
We are hiring a contract AI Engineer to build, deploy and maintain AI-enabled automations across our core systems stack. Working with the Principal Engineer and the Head of AI Operations, you will take prioritised automation opportunities from design through to production.
You will deliver against an internal AI roadmap spanning Customer Operations, Marketing, Finance, Education and Training to:<ul><li>Automate high-volume, manual administrative workflows</li><li>Build AI-enabled workflows in Salesforce, Zendesk, HubSpot, Zuora and Thrive LMS</li><li>Turn the Mission Control data platform into an engine for event-triggered automation</li><li>Reduce operational overhead and improve reporting speed and accuracy</li></ul>
Core ResponsibilitiesAutomation Build &amp; Integration<ul><li>Build and maintain automation pipelines using n8n, Zapier/Make and direct LLM API integrations (OpenAI/Anthropic)</li><li>Develop API and webhook integrations across Salesforce, Zendesk, HubSpot, Zuora and Thrive LMS</li><li>Implement workflows such as ticket summarisation, tagging, routing and AI triage</li></ul>
AI Engineering<ul><li>Design and implement RAG pipelines and vector database integrations over internal knowledge</li><li>Develop, test and version prompts; evaluate and improve output quality</li><li>Build event-triggered automations and AI-enabled reporting on Mission Control</li></ul>
Quality, Security &amp; Handover<ul><li>Apply sound engineering standards: error handling, logging and monitoring of automations in production</li><li>Ensure GDPR-compliant, secure handling of customer and company data</li><li>Document solutions clearly and hand over to internal teams for ongoing operation</li></ul>
What Success Looks Like (First 6 Months)<ul><li>Priority automation workflows live, stable and monitored in production</li><li>Measurable reduction in manual effort in targeted workflows</li><li>Reliable integrations across the core systems stack</li><li>Clear documentation enabling internal teams to operate and extend what you build</li></ul>
Required ExperienceTechnical<ul><li>Proven delivery of LLM-based automation in production environments</li><li>Strong experience with automation platforms (n8n, Make or Zapier)</li><li>Proficiency in Python and SQL</li><li>Strong API and webhook integration capability</li><li>Experience working with OpenAI/Anthropic APIs and prompt engineering</li><li>Experience building RAG pipelines and working with vector databases</li><li>Experience automating CRM (Salesforce) and support (Zendesk) environments preferred</li></ul>
Delivery<ul><li>Experience operating in B2B SaaS or similar fast-moving environments</li><li>Track record of delivering as a contractor: scoping, building and handing over cleanly</li><li>Comfortable working with non-technical stakeholders to refine requirements</li></ul>
Personal Attributes<ul><li>Delivery-focused and pragmatic</li><li>High agency and accountability</li><li>Structured, with strong attention to reliability and security</li><li>Comfortable working in ambiguity</li><li>Clear communicator with technical and non-technical audiences</li></ul>
Why This Role Matters
AI will be a structural margin lever for ASG. The automations you build will directly reduce operational cost, increase capacity without incremental headcount, and embed AI as core operational infrastructure rather than experimentation.</div>

AI Engineer (Contract)

Premier Group

<div>
 
 5+ years' experience in software engineering, with a strong background in scalable architecture and system design.
 
 
 
 
 
 Expert-level proficiency in
 
 TypeScript
 
 , including advanced typing techniques, reusable abstractions, and writing clean, maintainable code.
 
 
 
 
 
 Commercial experience building modern front-end applications using
 
 React
 
 , particularly for interactive dashboards, editing tools, or operational interfaces.
 
 
 
 
 
 Practical experience developing AI-powered applications using TypeScript-based frameworks such as
 
 LangChain.js
 
 ,
 
 LangGraph.js
 
 ,
 
 Vercel AI SDK
 
 , or equivalent custom LLM/agent frameworks.
 
 
 
 
 
 Solid understanding of autonomous agent architectures, including multi-agent workflows, task planning, orchestration, hierarchical agents, and execution pipelines.
 
 
 
 
 
 Experience designing and building APIs, SDKs, or service layers that enable automation and programmatic interaction with complex platforms.
 
 
 
 
 
 Strong understanding of prompt engineering best practices, including structured outputs, tool/function calling, retrieval patterns, and techniques for improving LLM reliability.
 
 
 
 
 
 Experience integrating AI capabilities into user-facing products, particularly where creative workflows or intelligent automation are involved.
 
</div>

Talan

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
As our AI practice scales, we are seeking an experienced AI Architect / Engineer to act as the senior technical authority shaping how we design and deliver next-generation AI solutions. This is a role for someone who has moved beyond building individual models to architecting entire systems: agentic platforms, LLM-powered applications, and the production infrastructure that makes them dependable at enterprise scale.
You will sit at the intersection of strategy and delivery, operating across multiple client engagements simultaneously. In the early phases you will shape solutions, validate technical approaches, and translate ambiguous business problems into robust, deployable architectures. As engagements mature, you will provide the technical oversight that keeps delivery teams aligned to the original design intent. Your influence will be felt in pre-sales conversations, solution blueprints, and the technical standards that define how our practice builds.
This is a hands on architectural role, not a purely advisory one. We expect you to remain close to the code, to prototype where it accelerates a decision, and to set a credible technical example for the engineers and data scientists you guide.
Required skills &amp; experience:<ul><li>
Lead end-to-end solution architecture for AI and LLM-based systems, spanning data, integration, infrastructure, and deployment.</li><li>
Design agentic architectures and multi-agent orchestration patterns, defining how LLMs, tools, APIs, and retrieval layers interact reliably.</li><li>
Shape early-stage engagements (scoping, solutioning, estimation, and pre-sales) turning client ambition into deliverable technical plans.</li><li>
Provide technical validation and quality oversight across several concurrent projects, mitigating risk before it reaches delivery.</li><li>
Define LLM integration and prompting strategies, including RAG, fine-tuning, evaluation, and guardrailing approaches.</li><li>
Establish MLOps and LLMOps practices that ensure solutions are observable, testable, and production ready.</li><li>
Set architectural standards, reusable patterns, and reference implementations that raise the quality bar across the practice.</li><li>
Partner with Responsible AI colleagues to embed safety, security, and governance into solution designs from the outset.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Minimum 5 years in AI architecture or AI engineering, ideally 10+, with a track record of production deployments.</li><li>
Deep expertise in LLMs, agent frameworks (e.g. LangGraph, AutoGen, Semantic Kernel), API design, and orchestration.</li><li>
Strong cloud engineering experience.</li><li>
Proven MLOps / LLMOps capability &mdash; CI/CD for models, monitoring, evaluation, and cost optimisation.</li><li>
Hands-on software engineering background (Python and modern tooling) underpinning your architectural decisions.</li><li>
Comfort managing multiple engagements at once, with pragmatic judgement on trade-offs and delivery risk.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Experience in consulting, professional services, or pre-sales environments.</li><li>
Exposure to enterprise-scale, regulated AI deployments (financial services, public sector, healthcare).</li><li>
Familiarity with vector databases, knowledge graphs, and advanced retrieval techniques.</li><li>
Relevant cloud or AI certifications.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul> 
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
You will be a founding technical voice in a practice that is investing decisively in AI. The work is varied, intellectually demanding, and commercially significant, you will shape solutions that reach production, not slideware. You will have the autonomy to define how we build, the support of a collaborative multidisciplinary team, and a clear platform to grow into a practice-leading technical figure.</div>

AI Architect / Engineer (Agentic AI & LLM Architecture)

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

<div>
 This role is with one of Dex's trusted partner companies. We work closely with their teams to truly understand their culture, goals, and what they're looking for, so we can match you with the right opportunity and give you context about the role before you commit to a process.
 
 
 
 If you're interested sign up to Dex to apply.
 
 
 
 Dex is an AI recruiter agent that helps you run your job search. Tell Dex your stack, seniority, and what you want to build. We will manage your applications and surface other opportunities that are a fit.
 
 
 
 The role
 
 
 
 This isn't another AI startup building a chatbot. This is a company acquiring profitable, mission-critical B2B SaaS businesses, then deploying a proprietary AI operating system across them. The goal: encode operational knowledge, automate workflows, and compound intelligence across a growing portfolio. The founding team brings deep experience from early-stage, pre-IPO Palantir and frontier AI research.
 
 
 You'll join a small engineering team tackling genuinely hard problems. This is end-to-end ownership: from architecture to production. It's not about maintaining legacy systems or shipping minor features. You'll build the core platform that ingests everything from CRM to financial records, or you'll deploy forward into acquired companies, shipping product changes identified by the intelligence layer. You'll shape what gets built, working directly with product and commercial teams. This is a rare seat for an engineer who wants to build, not just code.
 
 
 
 The work
 
 
 
 <ul>
 <li>
 Take end-to-end ownership of features, from architecture design to production deployment.
 </li>
 <li>
 Design APIs, data models, and integrations in Ruby and Python to ingest structured and unstructured data from acquired companies.
 </li>
 <li>
 Build React interfaces that surface real-time operational intelligence and enable autonomous agent workflows.
 </li>
 <li>
 Work directly with product and commercial teams to define and shape the core platform or forward-deployed product changes.
 </li>
 <li>
 Deploy product changes into group companies, acting on insights identified by the AI intelligence layer.
 
 
 </li>
 </ul>
 
 What You Bring
 
 
 
 <ul>
 <li>
 2-5 years of experience building and shipping production systems, owning the full lifecycle (data modelling, API design, testing, reliability, deployment).
 </li>
 <li>
 Strong in at least one modern stack, with the ability to quickly pick up new languages (the codebase is 90%+ Ruby).
 </li>
 <li>
 A track record of breaking down ambiguous problems, prioritising high-leverage work, and communicating technical reasoning clearly to non-engineers.
 </li>
 <li>
 Active exploration of AI tooling, LLM workflows, or developer productivity improvements, with something you can point to that you've built or shipped.
 </li>
 <li>
 You must be eligible to work in the UK and able to work from London in 2026.
 
 
 </li>
 </ul>
 
 Why apply through Dex
 
 
 
 This is a rare role at a company solving a genuinely hard problem, not just another oversubscribed posting. Dex helps you cut through the noise: get properly briefed on the full context, skip cold applications, and get matched to this role and others like it, all in one place.
 
 
 If you're interested, sign up to Dex to apply - https://jobs.meetdex.ai/jobs/c8715e68-23bc-4e9d-a8fc-61ae9ca444b1
 
 
 
 As part of the recruitment process at Dex, we process your personal data in accordance with our Privacy Notice for Job Applicants. This notice explains how and why your data is collected and used, and how you can contact us if you have any concerns.
 
</div>

Software Engineer (up to £150k)

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

Explore 81+ Ai engineer in London this July. Find roles across top companies and apply now to boost your career.

81 ai engineer jobs In London

AI Engineer

AI Engineer (Contract)

AI Engineer

AI Architect / Engineer (Agentic AI & LLM Architecture)

Senior Machine Learning Engineer - Customer AI

Software Engineer (up to £150k)

AI/ML Computational Science Senior Manager