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- Tasks: Lead the design and deployment of ML solutions, mentoring junior engineers along the way.
- Company: Data Reply is a dynamic analytics firm helping clients leverage data for impactful outcomes.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Join a cutting-edge team focused on AI innovation and make a real impact in the tech world.
- Qualifications: You need a degree in Computer Science or related field and 3+ years in MLOps/ML Engineering.
- Other info: We value diversity and are committed to creating an inclusive workplace for all.
The predicted salary is between 54000 - 84000 £ per year.
Senior MLOps / Machine Learning Engineer: LLMs & Agentic AI
Senior MLOps / Machine Learning Engineer: LLMs & Agentic AI
Senior MLOps / Machine Learning Engineer: LLMs & Agentic AI
About Data Reply:
Data Reply is the Reply Group company offering a broad range of analytics and data processing services. We operate across different industries and business functions, working directly with executive level professionals, enabling them to achieve meaningful outcomes through effective use of data. We find that one of the biggest problems experienced by our clients today is being overwhelmed with the amount of data that they face and not knowing how to leverage it to their advantage. The vast landscape of available technology stacks and models means that choosing the right ones can be a daunting task. Most companies know that their data is valuable, and that they should be making the most out of it to stay competitive, but often don\’t know where to begin or what to prioritise. At Data Reply, we pride ourselves on helping clients make the right decisions to build their data strategy. With our consultants\’ expertise, we map the right technologies to meet our clients\’ business needs. We deal in bespoke solutions, and offer in house training to ensure that our clients realise the full value of their big data solution. Overview:
As a Senior MLOps / ML Engineer at Data Reply, you will take ownership of architecting and deploying ML and GenAI solutions. You\’ll be hands-on at every stage – from proof-of-concept through production – and you\’ll help mentor junior AI engineers. A particular focus will be on deploying large-language models (LLMs) and AI agents at scale, integrating them with enterprise workflows, and ensuring repeatable, cost-efficient AWS architectures.
Responsibilities:
- Leading solution workshops to design scalable ML systems on AWS using services like VPC, IAM, SageMaker Studio, Lambda, and EKS
- You\’ll build CI/CD pipelines using GitHub Actions, Jenkins, and AWS CodePipeline for deploying traditional ML, GenAI models, and AI agents
- Deploying LLMs (e.g., via Huggingface) and construct AI agent workflows using tools like LangChain, LangGraph, and custom orchestrators
- Your expertise will help reduce cloud costs with GPU acceleration, auto-scaling, and spot instances
- To implement model lifecycle tools (MLflow, SageMaker Registry), performance dashboards, alerts, and automated retraining pipelines
- Connecting ML models to client systems using APIs, Kafka, and build agent workflows with vector databases (Pinecone, Weaviate)
- You\’ll enforce secure, compliant, and ethical practices-VPC design, IAM policies, data encryption, and adherence to GDPR
- You\’ll be a trusted advisor and mentor, presenting technical solutions, managing expectations, and guiding junior team members
About the candidates:
- University degree in Computer Science, Mathematics or in a directly related field (2.1 min grade)
- 3+ years in MLOps/ML Engineering experience, plus 5+ years in Python software development or data science
- Skilled in SageMaker (training, endpoints, pipelines), Lambda, Step Functions, S3, and CloudWatch
- Proficiency with Terraform or AWS CDK, Docker, and Kubernetes (EKS/Fargate)
- Experienced with MLflow (or alternatives), GitHub Actions, Jenkins, AWS CodePipeline, and automated testing
- You\’ve got hands-on experience with deploying LLMs and building AI agents using LangChain or custom frameworks
- Strong background in building data pipelines with Airflow/dbt and managing features via Feast or similar tools
- You have experience building dashboards with CloudWatch/Prometheus/Grafana and implementing data validation with Great Expectations
- It would be beneficial to have exposure to consulting/presales, MCP deployment, Databricks, and AWS ML Specialty certified
Reply is an Equal Opportunities Employer and committed to embracing diversity in the workplace. We provide equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type regardless of age, sexual orientation, gender, identity, pregnancy, religion, nationality, ethnic origin, disability, medical history, skin colour, marital status or parental status or any other characteristic protected by the Law.
Reply is committed to making sure that our selection methods are fair to everyone. To help you during the recruitment process, please let us know of any Reasonable Adjustments you may need.
With more than 16,000 experts in over 150 companies worldwide, Reply is a company that specialises in Consulting, Systems Integration and Digital Serv…
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Senior MLOps / Machine Learning Engineer: LLMs & Agentic AI | London, UK employer: Reply
Contact Detail:
Reply Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior MLOps / Machine Learning Engineer: LLMs & Agentic AI | London, UK
✨Tip Number 1
Familiarise yourself with the specific AWS services mentioned in the job description, such as SageMaker, Lambda, and EKS. Having hands-on experience or projects that showcase your skills with these tools will make you stand out during discussions.
✨Tip Number 2
Engage with the MLOps community by attending meetups or webinars focused on LLMs and AI agents. Networking with professionals in the field can provide insights and potentially lead to referrals for the position.
✨Tip Number 3
Prepare to discuss your experience with CI/CD pipelines and how you've implemented them in past projects. Being able to articulate your approach to deploying ML models efficiently will demonstrate your expertise.
✨Tip Number 4
Showcase your mentoring experience by preparing examples of how you've guided junior engineers in previous roles. This will highlight your leadership skills, which are crucial for the Senior MLOps role.
We think you need these skills to ace Senior MLOps / Machine Learning Engineer: LLMs & Agentic AI | London, UK
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in MLOps and Machine Learning Engineering. Focus on your hands-on experience with AWS services, LLMs, and AI agents, as well as any leadership roles you've held.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data and AI. Mention specific projects where you've successfully deployed ML solutions and how you can contribute to Data Reply's mission of helping clients leverage their data effectively.
Showcase Technical Skills: Clearly list your technical skills related to the job description, such as proficiency in Python, SageMaker, Terraform, and CI/CD tools. Provide examples of how you've used these technologies in past projects.
Highlight Mentorship Experience: Since the role involves mentoring junior engineers, include any relevant experience you have in guiding or training others. This could be formal mentorship or simply leading teams in projects.
How to prepare for a job interview at Reply
✨Showcase Your Technical Skills
Be prepared to discuss your experience with MLOps and ML engineering, particularly with AWS services like SageMaker, Lambda, and EKS. Bring examples of projects where you've deployed LLMs or built AI agents, as this will demonstrate your hands-on expertise.
✨Understand the Company’s Needs
Research Data Reply and their approach to data strategy. Understand the challenges they face with data management and be ready to discuss how your skills can help solve these issues. Tailoring your answers to align with their mission will show that you're genuinely interested.
✨Prepare for Problem-Solving Questions
Expect to encounter scenario-based questions that assess your problem-solving abilities. Practice articulating your thought process when designing scalable ML systems or optimising cloud costs, as this will highlight your analytical skills and practical knowledge.
✨Demonstrate Leadership and Mentorship
Since the role involves mentoring junior engineers, be ready to share your experiences in guiding others. Discuss how you’ve led workshops or training sessions, and emphasise your ability to communicate complex concepts clearly and effectively.
