Senior MLOps / Machine Learning Engineer: LLMs & Agentic AI

Reply; London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading tech company in London is seeking an experienced MLOps/ML Engineer to design scalable ML systems on AWS. This role involves leading workshops, building CI/CD pipelines, and connecting ML models to client systems. Candidates should have at least 3 years in MLOps and 5 years in Python development. Proficiency in AWS services like SageMaker and Lambda is essential. The position offers opportunities for mentorship and career growth.

Qualifications

• University degree in Computer Science, Mathematics, or a related field (minimum grade).
• 3+ years of experience in MLOps/ML Engineering and 5+ years in Python software development or data science.
• Proficient in SageMaker, Lambda, Step Functions, S3, and CloudWatch.
• Skilled in Terraform or AWS CDK, Docker, and Kubernetes.
• Experienced with MLflow, GitHub Actions, Jenkins, AWS CodePipeline, and automated testing.
• Hands-on experience deploying LLMs and building AI agents using LangChain.
• Strong background in building data pipelines with Airflow/dbt.
• Experience creating dashboards with CloudWatch/Prometheus/Grafana.

Responsibilities

• Leading solution workshops to design scalable ML systems on AWS.
• Building CI/CD pipelines for deploying ML models.
• Deploying LLMs and constructing AI agent workflows.
• Optimizing cloud costs through various AWS strategies.
• Implementing model lifecycle tools, performance dashboards, and automated retraining pipelines.
• Connecting ML models to client systems using APIs and Kafka.

Job description

Responsibilities:

• Leading solution workshops to design scalable ML systems on AWS using services like VPC, IAM, SageMaker Studio, Lambda, and EKS.
• Building CI/CD pipelines with GitHub Actions, Jenkins, and AWS CodePipeline for deploying traditional ML, GenAI models, and AI agents.
• Deploying LLMs via Huggingface and constructing AI agent workflows using tools like LangChain, LangGraph, and custom orchestrators.
• Optimizing cloud costs through GPU acceleration, auto-scaling, and spot instances.
• Implementing model lifecycle tools (MLflow, SageMaker Registry), performance dashboards, alerts, and automated retraining pipelines.
• Connecting ML models to client systems using APIs, Kafka, and building agent workflows with vector databases like Pinecone and Weaviate.
• Ensuring secure, compliant, and ethical practices through VPC design, IAM policies, data encryption, and GDPR adherence.
• Serving as 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 a related field (minimum grade).
• 3+ years of experience in MLOps/ML Engineering and 5+ years in Python software development or data science.
• Proficient in SageMaker (training, endpoints, pipelines), Lambda, Step Functions, S3, and CloudWatch.
• Skilled in Terraform or AWS CDK, Docker, and Kubernetes (EKS/Fargate).
• Experienced with MLflow (or alternatives), GitHub Actions, Jenkins, AWS CodePipeline, and automated testing.
• Hands-on experience 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.
• Experience creating dashboards with CloudWatch/Prometheus/Grafana and implementing data validation with Great Expectations.
• Beneficial to have exposure to consulting/presales, MCP deployment, Databricks, and AWS ML Specialty certification.

Reply is an Equal Opportunities Employer committed to embracing diversity in the workplace. We provide equal employment opportunities to all employees and applicants and prohibit discrimination and harassment of any kind regardless of age, sexual orientation, gender, identity, pregnancy, religion, nationality, ethnic origin, disability, medical history, skin colour, marital status, or parental status. We are committed to fair recruitment practices. Please inform us of any reasonable adjustments needed during the recruitment process.

Job ID 10760