Machine Learning Ops Engineer, Opus 2

Artificial Intelligence

Salary not provided

+ Loyalty Share Scheme

AWS

Docker

Kubernetes

TypeScript

GCP

Python

Java

Terraform

Azure

Prometheus

Grafana

Sagemaker

DevOps

Mid and Senior level

London

Legal software & services

Job no longer available

Legal software & services

201-500 employees

B2BData storageLegalCommunication

Job no longer available

Salary not provided

+ Loyalty Share Scheme

AWS

Docker

Kubernetes

TypeScript

GCP

Python

Java

Terraform

Azure

Prometheus

Grafana

Sagemaker

DevOps

Mid and Senior level

London

201-500 employees

B2BData storageLegalCommunication

Company mission

To design, develop, and deliver industry-leading solutions that transform the dispute lifecycle —empowering legal professionals to maximise the value they deliver to clients.

Job

Company

Role

Who you are

You are a practical and automation-driven engineer. You think in terms of reliability, scalability, and efficiency
You have hands-on experience building and managing CI/CD pipelines for machine learning
You're comfortable writing production-quality code, reviewing PR's, and are dedicated to delivering a reliable and observable production environment
You are passionate about MLOps and have a proven track record of implementing MLOps best practices in a production setting
You’re curious about the unique operational challenges of LLMs and want to build robust systems to support them
Experience with model lifecycle management and experiment tracking
Ability to reason about and implement infrastructure for complex AI systems, including those leveraging vector stores and graph databases
Proven ability to ensure the performance and reliability of systems over time
3+ years of experience in an MLOps, DevOps, or Software Engineering role with a focus on machine learning infrastructure
Proficiency in Python, with experience in building and maintaining infrastructure and automation, not just analyses
Experience working in Java or TypeScript environments is beneficial
Deep experience with at least one major cloud provider (AWS, GCP, Azure) and their ML services (e.g., SageMaker, Vertex AI). Experience with Amazon Bedrock is a significant plus
Strong familiarity with containerization (Docker) and orchestration (Kubernetes)
Experience with Infrastructure as Code (e.g., Terraform, CloudFormation)
Experience in deploying and managing LLM-powered features in production environments
Bonus: experience with monitoring tools (e.g., Prometheus, Grafana), agent orchestration, or legaltech domain knowledge

What the job involves

Design, build, and maintain our MLOps infrastructure, establishing best practices for CI/CD for machine learning, including model testing, versioning, and deployment
Develop and manage scalable and automated pipelines for training, evaluating, and deploying machine learning models, with a specific focus on LLM-based systems
Implement robust monitoring and logging for models in production to track performance, drift, and data quality, ensuring system reliability and uptime
Collaborate with Data Scientists to containerize and productionize models and algorithms, including those involving RAG and Graph RAG approaches
Manage and optimize our cloud infrastructure for ML workloads on platforms like Amazon Bedrock or similar, focusing on performance, cost-effectiveness, and scalability
Automate the provisioning of ML infrastructure using Infrastructure as Code (IaC) principles and tools
Work closely with product and engineering teams to integrate ML models into our production environment and ensure seamless operation within the broader product architecture
Own the operational aspects of the AI lifecycle, from model deployment and A/B testing to incident response and continuous improvement of production systems
Contribute to our AI strategy and roadmap by providing expertise on the operational feasibility and scalability of proposed AI features
Collaborate closely with Principal Data Scientists and Principal Engineers to ensure that the MLOps framework supports the full scope of AI workflows and model interaction layers

Salary benchmarks

Our take

Documentation, clients and teams are all multifarious in legal proceedings, and therefore provide unique logistical problems. Opus 2 aims to meet the needs of the modern courtroom by providing digital solutions in an age of remote hearings.

The company provides e-bundles that seek to solve these problems. Whilst courtrooms may use existing video software to conduct hearings, Opus 2 integrates this software with other elements (such as data storage and documentation) in order to streamline the process and ultimately save time for everyone. The company offers virtual workspaces on a secure cloud platform, streamlining legal work for both lawyers and clients.

Opus 2 continually invests in developing its software in the UK and internationally and facilitates this by hiring new talent. A recent partnership with SeeUnity is set to help achieve this.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

13% employee growth in 12 months

Glassdoor (4.3)

Company

Company HQ

Holborn, London, UK

Leadership

Graham Smith-Bernal

(CEO)

Founded LiveNote, the world's most widely used litigation support tool, before starting Opus 2 in 2008.

Share this job

View 5 more jobs at Opus 2