AgileGrid Solutions
ML/AI Engineer

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About The Company
Lloyds Banking Group is one of the leading financial services organizations in the United Kingdom, renowned for its commitment to innovation, customer-centric solutions, and corporate responsibility. With a rich history spanning over a century, the group has continuously evolved to meet the changing needs of its customers, businesses, and communities. Lloyds Banking Group offers a comprehensive range of banking and financial services, including retail banking, commercial banking, and wealth management, supported by a strong digital infrastructure that drives efficiency and accessibility. The organization is dedicated to fostering a diverse and inclusive workplace, ensuring that all employees feel valued, empowered, and equipped to contribute to the company's ongoing success. As a forward-thinking institution, Lloyds Banking Group invests heavily in technology, data, and talent to shape the future of financial services and promote sustainable growth across the UK.
About The Role
We are seeking a highly skilled and motivated Machine Learning/Artificial Intelligence (ML/AI) Engineer to join our Data & AI Engineering team in Manchester. This full-time position offers an exciting opportunity to work at the forefront of AI innovation, supporting the development, deployment, and maintenance of scalable machine learning systems. As an ML/AI Engineer, you will be responsible for building automated pipelines, managing large-scale model deployment, and ensuring the reliability and efficiency of AI services. You will lead initiatives around Kubernetes orchestration, CI/CD automation using Harness, GPU optimization, and model lifecycle management, from code commit to production release. This role provides a unique platform to embed fairness, transparency, and accountability into AI solutions, shaping the future of responsible AI within the organization. The position is ideal for passionate engineers eager to make a significant impact through innovative technology and data-driven solutions, contributing to Lloyds Banking Group's transformation into a data-led organization.
Qualifications
The ideal candidate will possess a strong technical background in Python programming, with expertise in automation, tooling, and service development. Extensive experience in Kubernetes, Docker, Helm, and related orchestration tools is essential, along with a deep understanding of autoscaling, resource management, and node-pool configurations. Proven proficiency in CI/CD pipelines, especially with Harness or similar platforms, is required, along with hands-on experience with GitOps practices and environment promotion strategies. Practical knowledge of GPU technologies, including CUDA, TensorRT, Triton, and TorchServe, is highly desirable. Candidates should have a solid understanding of observability tools such as Prometheus, Grafana, and Dynatrace, and experience operating MLflow or equivalent systems for experiment tracking and model management. Familiarity with cloud platforms like GCP, including GKE, Cloud Run, and Vertex AI, as well as frameworks like Ray or Kubeflow, will be advantageous. The role also requires strong collaboration skills, problem-solving ability, and a passion for continuous learning and innovation.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Responsibilities
Your primary responsibilities will include designing, building, and operating production-grade Kubernetes clusters capable of handling high-volume model inference and scheduled training jobs. You will configure autoscaling, resource quotas, GPU/CPU node pools, and service mesh components to optimize reliability and efficiency. Developing and implementing GitOps workflows for environment configuration and application deployment will be key, alongside building CI/CD pipelines in Harness to automate build, test, and deployment processes across multiple environments. You will enable progressive delivery strategies such as blue/green and canary deployments, incorporating quality gates and model evaluation checks to ensure safe rollouts. Standardizing pipelines for continuous training and monitoring will help keep models current and safe in production. You will deploy and fine-tune GPU-backed inference services, optimize CUDA environments, and leverage TensorRT for performance improvements. Ensuring comprehensive observability by monitoring drift, data quality, fairness signals, latency, and GPU utilization is crucial, utilizing tools like Prometheus, Grafana, and Dynatrace. You will establish alerting protocols, incident management procedures, and reliability improvements, as well as operate model registries with versioning, lineage, and environment-specific artifacts. Additionally, enforcing audit readiness through model cards, reproducible builds, and provenance tracking will be part of your role, ensuring compliance and transparency throughout the AI lifecycle.


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Benefits
Lloyds Banking Group offers a comprehensive benefits package designed to support the wellbeing and professional growth of its employees. This includes a generous pension contribution of up to 15%, an annual performance-based bonus, and share schemes that may include free shares. Employees can take advantage of flexible benefits such as discounted shopping, 30 days of holiday plus bank holidays, and a variety of wellbeing initiatives aimed at promoting a healthy work-life balance. The organization also provides generous parental leave policies and opportunities for continuous learning and development. The company fosters a collaborative and inclusive environment where innovation is encouraged, and employees are empowered to make meaningful contributions. With a focus on diversity and inclusion, Lloyds Banking Group strives to create a workplace where everyone feels valued and able to thrive.
Equal Opportunity
Lloyds Banking Group is committed to fostering an inclusive environment where all individuals are treated with respect and fairness. We actively promote diversity and welcome applications from all backgrounds, especially from under-represented groups. The organization is disability confident and offers reasonable adjustments to support candidates throughout the recruitment process. Our commitment to equality ensures that every employee has the opportunity to succeed, contribute, and grow within the company. We believe that a diverse workforce enhances our ability to serve our customers effectively and drives innovation across our organization.
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