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- Tasks: Lead the design and deployment of ML solutions, mentoring junior engineers along the way.
- Company: Data Reply offers innovative analytics and data processing services across various industries.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Join a dynamic team tackling real-world data challenges with cutting-edge technology and impactful solutions.
- Qualifications: University degree in a relevant field and 3+ years in MLOps/ML Engineering required.
- Other info: We embrace diversity and provide equal opportunities for all applicants.
The predicted salary is between 43200 - 72000 £ per year.
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. www.data.reply.com
Role 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. #J-18808-Ljbffr
Senior MLOps / Machine Learning Engineer: LLMs & Agentic AI 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
✨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
Prepare to discuss your experience with deploying large language models (LLMs) and AI agents. Be ready to share examples of how you've integrated these technologies into workflows, as this is a key focus for the role.
✨Tip Number 3
Highlight any mentoring or leadership experiences you have, especially in guiding junior engineers. This role involves being a trusted advisor, so demonstrating your ability to lead and support others will be beneficial.
✨Tip Number 4
Stay updated on the latest trends and best practices in MLOps and AI deployment. Being knowledgeable about current technologies and methodologies will help you engage in meaningful conversations during the interview process.
We think you need these skills to ace Senior MLOps / Machine Learning Engineer: LLMs & Agentic AI
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 any specific tools mentioned in the job description.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and data solutions. Mention specific projects where you've deployed ML models or built data pipelines, and explain how your skills align with Data Reply's mission.
Showcase Technical Skills: In your application, emphasise your proficiency with tools like SageMaker, Terraform, and Docker. Provide examples of how you've used these technologies to solve real-world problems in previous roles.
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 sharing knowledge within your team.
How to prepare for a job interview at Reply
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with MLOps and ML engineering. Highlight specific projects where you've deployed large-language models or built AI agents, and be ready to explain the technologies you used, such as AWS services, GitHub Actions, and Docker.
✨Demonstrate Problem-Solving Skills
Data Reply values the ability to tackle complex data challenges. Prepare examples of how you've helped clients overcome data-related issues, particularly in designing scalable ML systems or optimising cloud costs. Use the STAR method (Situation, Task, Action, Result) to structure your responses.
✨Emphasise Mentorship Experience
As a Senior MLOps/ML Engineer, you'll be expected to mentor junior engineers. Share your experiences in guiding others, whether through formal mentorship or collaborative projects. Discuss how you approach teaching complex concepts and fostering a supportive learning environment.
✨Understand Data Reply's Values
Familiarise yourself with Data Reply's mission and values, especially their commitment to diversity and ethical practices. Be ready to discuss how you align with these values and how you can contribute to creating an inclusive workplace while ensuring compliance with data regulations.
