differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results. Title and Summary Lead MLOps Engineer Lead MLOps Engineer Overview We are looking for a lead MLOps engineer to join an award winning team with a proven track record of … lifecycle, with a focus on the role of ML. Role • The team is experienced in building applications around ML models, this is the first MLOps specific role, to specialise as we scale. • The focus will be on implement a full ML workflow from scratch, following Mastercard guidelines and using approved … understand how to build and operate deployment pipelines. • You can debug products end to end through logs and error messages. • You have implemented an MLOps workflow. • You have experience with monitoring models and creating actions from feature creep and model entropy. • Experience of working within Agile frameworks including Scrum and more »
culture where employees can bring their authentic selves to work. Key responsibilities of the role are summarised below: We are seeking an experienced Hybrid MLOps, DevOps, Dev Engineer to lead multiple projects while providing high-level strategic guidance to our clients. This role requires exceptional client-facing skills and the … ability to handle multiple projects simultaneously. The successful candidate will be responsible for working closely with a DevOps team of 4 and 2 MLOps engineers, advising clients on their strategic goals, and assisting them in delivery. Responsibilities: Implementation of DevOps best practices Working knowledge of Istio, Argo CD, Argo Workflows more »
deployment. Solid understanding of SDLC and CI/CD processes. Desired : experience in Infrastructure as Code developments and tools e.g. Terraform Desired : experience with MLOps deployment and maintenance. Desired: Data Engineering technologies e.g. ETL , Spark , Dataflow , BigQuery Please note: even if you don't have exactly the background indicated, do more »
and results effectively to stakeholders.You will monitor and refine launched products to drive the roadmap.Qualifications:Experience in product management experience, with a focus on MLOps tooling.You have hands-on experience in Data Science or Software Engineering.Ability to work closely with engineers on technical architecture.Experience in UX HOW TO APPLYPlease register more »
and problem-solving skills Agile methodologies Coaching and mentoring Modern technologies like cloud-native, containers, and serverless Desirable: Knowledge of frontend technologies and frameworks MLOps knowledge What is in it for you? 27 days of annual leave Healthy half (0.5 day leave every 6 months for wellbeing) Study/volunteer more »
list. Nice to have: Experience of architecting systems and designing APIs Knowledge of structured databases such as PostgreSQL Experience with machine learning applications and MLOps Understanding of working on embedded/resource-constrained devices Flexibility to travel and work with customers on-site when appropriate All engineers at Arondite are more »
environments. Proficiency or experience with Apache Spark. Familiarity or background in working with Azure. Experience orchestrating workflows, particularly within distributed system environments. Knowledge of MLOps principles and practices, especially in implementing them within production settings. Why Monolith? Our culture is passionate, engaging and collaborative. We are genuine, we bring our more »
MLOps Engineer Up to 100k Hybrid - London 2/3 days a week My Client is a global luxury retailer looking for an MLOps Engineer to join their strong AI department, where you will help build and maintain the ML infrastructure as well as supporting the deployment and productionisation of … reliability of the ML systems. Apply software engineering principles Work cross functionally across the business What you need to succeed: Strong background as a MLOps Engineer, Platform Engineer or Devops Engineer Must have experience working on ML infrastructure using Docker and Kubernetes Minimum of 3 to 5 years experience Extensive more »
Company Description We are champions of rail, inspired to build a greener, more sustainable future of travel. Our purpose is our momentum. It makes us feel good because we know we re doing good. As we lead the way to more »
ll be working closely with Data Scientists and Software Engineers to develop and productionise a greenfield NLP product. Experience required (min. 5 years): NLP MLOps with Cloud (AWS w/SageMaker preferred, other clouds also considered) End-to-end ML experience Other details: Up to £650 per day outside IR35 more »
close collaboration with researchers a strong plus Experience with data driven python pipelines, data/ML platform design production model evaluation, and/or MLOps a strong plus Portfolio optimisation/market impact models/optimal execution/transaction cost analysis a strong plus Experience with production front office trading more »
/ML frameworks like TensorFlow and PyTorch. Automated model deployment and performance monitoring. Optimising GenAI solutions for performance and cost efficiency. LLMs, RAG, Guardrails, MLOps, and multi-modality. Experience with GenAI platforms (AWS Bedrock, Google Vertex, Langchain, LlamaIndex). As an AI Solution Architect you will be leading end to more »
deployment. Solid understanding of SDLC and CI/CD processes. Desired : experience in Infrastructure as Code developments and tools e.g. Terraform Desired : experience with MLOps deployment and maintenance. Desired: Data Engineering technologies e.g. ETL , Spark , Dataflow , BigQuery Please note: even if you don't have exactly the background indicated, do more »
Guildford, Surrey, South East, United Kingdom Hybrid / WFH Options
Allianz Insurance Plc
to develop advanced ML models and algorithms that power our data-driven solutions. To further strengthen our ML capabilities and streamline our ML operations (MLOps), we are seeking a skilled and motivated Platform Engineer to join our data science team. Role Overview As a Platform Engineer at Allianz Commercial, you … data scientists and data engineers to provision infrastructure and operationalize ML models and ensure their scalability, reliability, and performance. Your expertise in DevOps/MLOps and experience with the Azure cloud environment will be essential in designing and implementing end-to-end ML solutions. You will collaborate with cross-functional … production. This role requires strong technical skills, a solid understanding of Azure Cloud services and deployment/configuration processes, and experience with DevOps/MLOps best practices. Responsibilities Collaborate with data scientists and data engineers to understand ML requirements, and design and develop ML pipelines for data pre-processing, model more »
Manchester, North West, United Kingdom Hybrid / WFH Options
N Brown Group
We're looking for a Lead Machine Learning Engineer join our Data Engineering team. As the Lead ML Ops Engineer, you will be at the forefront of innovation, leading a small team of skilled engineers to develop and deploy scalable more »
MLOps Engineer (London – visit the office x3 days a week) Xcede are delighted to be working with a very exciting scale-up Tech Product organisation. With a fledgling Data Science team already in place who focus on recommendation systems and customer personalisation, the company now want to hire an MLOps … decision within the ML function – MLOps. Requirements Strong academic background in a relevant field (Statistics, Computer Science, etc.) Significant commercial experience deploying and maintaining (MLOps) Machine Learning algorithms and infrastructure. This would ideally be in a digital B2C product or platform. Some experience of deploying recommendation engines/recommender systems more »
results. Ability to apply ML solutions across various industries. Experience in full lifecycle model development, including compliance and security. Cloud-based ML deployment and MLOps expertise. Benefits: 26 days PTO + bank holidays Employee equity more »
structures to support analytics, research, or actuarial functions within an insurance company. Proficiency with cloud technologies such as Snowflake and Databricks. Familiarity with the MLOps framework. Ability to work independently, manage tasks, and engage team members effectively. Exceptional collaboration and relationship-building skills. Comfortable with handling ambiguous concepts and breaking more »
and requirements for deploying their work into production. Develop and enhance mechanisms and processes to streamline the integration of causal AI models into the MLOps workflow, customizing it to suit causality. Design and implement tools, visualizations, and mechanisms that empower data scientists to deploy their work into production autonomously, reducing … dependencies on additional teams or assistance. Work directly on integrating key elements of MLOps workflow with causal AI capabilities, ensuring robustness, scalability, and efficiency. Act as a subject matter expert on processes and best practices, providing guidance and support to data scientists on deployment and monitoring. Collaborate with cross-functional … significant exposure to deploying machine learning models into production. Strong proficiency in Python for both machine learning engineering and data science tasks. Experience with MLOps practices, including model deployment, monitoring, version control, and CI/CD pipelines. Proven experience in data pipelining, system architecture, and design for scalable and reliable more »
application. These include ingesting and understanding new data sources, evolving our data approach (e.g., to a fully fledged data fabric), implementing containers to streamline MLOps and exploring how we can sensibly and safely utilise artificial intelligence (AI) to turbo charge our work (e.g., smart data quality monitoring, meta data curation … desirable Utilising AI within data engineering to drive performance. Knowledge of implementing, managing and utilising graph databases (e.g., using technologies such as Neo4j). MLOps experience including familiarity with Docker and Kubernetes. Full data engineering cycle knowledge (tools and skills) for stream data. Benefits Competitive salary and rewards package including more »
JOB DESCRIPTION Working within the Advanced Analytics group at our company, you will provide technical expertise and leadership in the development of models and algorithms to provide strategic marketing recommendations. We are looking for a technical leader with mastery of more »
job listing link should always be relied on for authoritative information. About the company Weights & Biases Office Description Weights & Biases is a developer-first MLOps platform. Track everything you need to make your models reproducible with Weights & Biases from hyperparameters and code to model weights and dataset versions. Weights & Biases more »
Greater London, England, United Kingdom Hybrid / WFH Options
trg.recruitment
models (fraud detection, risk assessment) with a focus on NER. Leverage CI/CD & containers for seamless integration & scalability. Automate ML Workflows: Build robust MLOps pipelines to automate data ingestion, pre-processing, model training & serving for efficient NLP workflows. Champion NLP Expertise: Collaborate with data science teams, translate model requirements … of NLP models. We're Looking For: Proven experience building and deploying NLP models, strong grasp of statistics, ML techniques, and proficiency in Python. MLOps & Cloud Infrastructure: A strong understanding of CI/CD pipelines, containerisation technologies (Docker, Kubernetes), and cloud platforms (AWS, Azure, GCP). Degree in Computer Science more »
role: Architecting, building and maintaining ML processing pipelines/workflows in Python via technologies such as Spark, serverless functions, Airflow, MLflow, or other. Implement MLOps and related DevOps focused on creating ML workflows for deploying models for large scale inference and optimisations. Build Docker containers, in collaboration with Data Scientists … in large scale digital applications. Extensive experience with programming in Python, Jupyter notebooks, Spark, and Docker Professional experience of designing, building and managing bespoke MLOps in cloud environments, using tools such as SageMaker Processing, SageMaker Pipelines, Apache Airflow, and MLflow. Strong, fundamental technical expertise in cloud-native technologies, such as more »
SENIOR MLOPS ENGINEER HYBRID (LONDON) £80,000-£90,000 COMPANY: Our client is a leading digital healthcare company delivering a range of services directly to people's homes through innovative AI technology. With a rapidly growing teams, they are dedicated to improving healthcare access and outcomes for millions of individuals. more »
