151 to 175 of 198 MLOps Jobs in London

Experience fine‐tuning LLMs (e.g., LoRA, QLoRA, RLHF) specifically for domain‐specific enterprise applications. Taken responsibility of models from concept to production, utilising strong MLOps and LLMOps practices to ensure scalable, reliable, and monitorable deployments. High proficiency in Python and modern software development practices, including rigorous testing, code reviews … Computer Science, Artificial Intelligence, Statistics, Data Science, or a related quantitative field. Experience working with scalable cloud infrastructure (AWS, GCP, or Azure) and MLOps tools for model training, monitoring, and deployment. Background in forecasting, planning, or analytics applications. Familiarity with Anaplan or similar enterprise planning platforms. Experience with A/ ...

better systems that deliver real business value. Key Responsibilities Technical Leadership & Ownership (Individual Contributor) Act as the technical lead for Machine Learning Engineering and MLOps across London Market. Technically lead the most complex and business‐critical ML systems, from architectural design through to production operation. Define and evolve production … experience as a senior or principal Machine Learning Engineer delivering production ML systems at scale. Proven track record of owning or shaping ML platforms, MLOps frameworks, or critical ML infrastructure. Experience operating in complex, cross‐functional environments (insurance or financial services experience is advantageous but not essential). Technical Expertise ...

About Us Have you ever wanted to build something that doesn’t just improve the status quo, but makes it 100x better? Not just a small step forward, but a complete reinvention. That’s what ...

This is a fantastic opportunity to work as an MLOps Engineer on a remote basis, outside IR35, for a growing pharmaceutical company. The key skills required for this MLOps Engineer position are: MLOps AI AWS Python Terraform Kubernetes DevOps background If you do have the relevant experience for this long … term remote contract MLOps Engineer role, outside IR35, please do apply. ...

optimizing the ML systems that power drug discovery processes, ensuring scalability across vast datasets. The ideal candidate will have hands-on experience in infrastructure, MLOps, and distributed systems, and be excited to work with ML technologies. The position is hybrid, requiring office presence at least 50% of the time. Compensation ...

FHIR . Proven ability to engage with senior executives and carry significant sales targets. Preferred Skills Experience with multi-agent AI frameworks and MLOps for AI systems. Background in patient engagement tools or digital health solutions . Expertise in clinical trials , pharmacovigilance , or patient support services . Why Join ...

MLOps Engineer, Palantir Platform Fully Remote 6 Month Contract Outside IR35 £550 to £650 per day The Company They are a large, data driven organisation operating at scale, with a strong focus on using advanced analytics and machine learning to inform decision making. The business invests heavily in its data … platforms and engineering capability, creating an environment where robust MLOps practices are essential. Teams are collaborative, delivery focused and used to working with senior technical stakeholders. The Role and Deliverables Design, build and maintain MLOps pipelines on the Palantir Foundry platform. Enable reliable deployment, monitoring and retraining of machine learning ...

signal processing to deliver real-time audio quality improvements at scale — deployed across cloud, edge and embedded environments. The role A high-impact MLOps role owning end-to-end ML pipelines — from data through training, evaluation and deployment. You’ll work closely with audio ML researchers and DSP engineers … small ML team. What they’re looking for Proven experience building and operating production ML systems Strong Python and ML frameworks (PyTorch, TensorFlow) MLOps, CI/CD and model lifecycle management Cloud platforms (AWS, GCP or Azure) and containers/Kubernetes Experience with low-latency or real-time systems; familiarity ...

MLOps Platform Manager (Palantir) London Rate: £550-£650 Outside IR35 Per Day Work Type: Fully remote Start: ASAP The Company They are a well established organisation with a strong enterprise data estate and a clear commitment to using data and AI responsibly at scale. The business operates in a complex … central platform function focused on operational excellence. The Role and Deliverables Own the day to day operation of Palantir platforms and associated MLOps services, ensuring availability, performance and a strong user experience. Establish and run service management processes including incident, problem and change management, supported by clear documentation and runbooks. ...

understanding of the full ML lifecycle and strong software/platform instincts - you know what it takes to run reliable ML at scale – including MLOps tooling and practices Experience raising operational standards: SLIs/SLOs, monitoring, incident management, and production reliability Budget ownership, including infrastructure cost management and vendor oversight … associated ML/DS libraries (scikit-learn, NumPy, LightGBM, Pandas, LangChain/LangGraph, TensorFlow, etc.) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc MLOps/DevOps: Terraform, Docker, Airflow, MLFlow Monitoring and evaluation platforms including New Relic and Braintrust More information Enjoy fantastic perks like private healthcare & dental insurance ...

into advanced techniques, including LLMs, RAG architectures, and Generative AI applications to create new forms of automated analysis and augmented intelligence products. Production Engineering & MLOps : Translate validated prototypes into robust, production‐ready specifications, and lead the implementation of MLOps best practices (CI/CD, monitoring, serving) required for the reliable …/DL models. Experience with advanced analysis of unstructured or multi‐modal data (e.g., high‐dimensional feature vectors, dense embeddings) is highly valued. MLOps Mindset : Proven track record of transforming R&D proofs‐of‐concept into robust, scalable, and monitored production‐grade ML solutions. Engineering Rigor : A background in software ...

Role Summary We are seeking a Principal Machine Learning Engineer (SageMaker, MLOps, Model Governance & Explainability) to provide technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that … architecture for the matching platform, including data pipelines, model training workflows, inference runtimes, and telemetry ecosystems. Lead adoption of best‐in‐class MLOps patterns, platform tooling, and AWS SageMaker capabilities across training, processing, registry, monitoring, and deployment. Partner with platform, security, and data engineering teams to implement scalable data lakehouse ...

Establish a scalable AI runtime environment to support rapid prototyping and early deployment of LLM agents and agentic workflows.* Design and implement a robust MLOps stack with model versioning, CI/CD pipelines, and automated monitoring for operational resilience.* Build secure, compliant AI development and deployment architectures while aligning with … Qualifications:*** Proven leadership in designing scalable, cloud-native or hybrid AI/ML platforms that support experimentation and secure enterprise deployment.* Deep expertise in MLOps strategy and execution, including end-to-end pipelines, CI/CD, model versioning, and retraining workflows.* Hands-on experience with model deployment and runtime management ...

scenario studies, and clear articulation of trade‐offs. Lead development of ML/AI solutions end‐to‐end (feature engineering, model training/validation, MLOps, monitoring and drift management) with rigorous controls, documented governance, and demonstrable business value. Uphold standards for documentation, reproducibility, traceability, and SDLC; ensure compliance with internal … governance, and regulatory expectations for pricing/risk models. Hands‐on ML/AI for quant finance (signal extraction, surrogate modelling, anomaly detection), including MLOps, drift monitoring, and explainability. Knowledge of portfolio optimisation, hedging algorithms, execution analytics, and transaction cost modelling. Familiarity with distributed computing and market data tooling (e.g. ...

underpins AI and machine learning delivery . This is a hands-on senior platform role , focused on building robust, Kubernetes-based platforms that enable MLOps engineers, ML engineers, and data scientists to deploy, run, and manage models safely and effectively in production. While you'll need a strong understanding … just running clusters. You will: Design, build, and operate a Kubernetes-based platform that supports multiple ML and engineering teams Extend Kubernetes with MLOps-specific capabilities , rather than treating it as a finished product Provideplatform-level support for: Model development and experimentation Model packaging, deployment, and promotion Scalable inference ...

models across Recursion’s massive datasets and deep learning workloads. Act as a mentor, coach, and sponsor – share technical, leadership and managerial skills in MLOps, distributed computing, and infrastructure engineering to drive impact, learning, and growth across teams. Enable a model‐driven culture – work with stakeholders to ensure … improvement. The Team You’ll Join: You’ll be part of a group of technical leaders who collaborate on engineering leadership, ML system architecture, MLOps patterns, and infrastructure optimization. The team tackles model scalability, deployment reliability, and infrastructure efficiency across the company. The Experience You Will Need: Hands‐on tech ...

solutions for model development, training, and deployment. Act as a mentor, coach, and sponsor – You will share your technical, leadership and managerial skills in MLOps, distributed computing, and infrastructure engineering, delivering impact, learning, and growth across teams at Recursion. We believe that the best work comes from working across organizational … deployment, and continuous improvement. Problems you will work on could range from optimizing GPU cluster utilization to implementing Agentic orchestration and establishing company-wide MLOps standards. The Team You’ll Join: You’ll be part of a group of technical leaders who work together on the craft of engineering leadership ...

Backend Software Engineer/Developer (Python LLM MLOps) London/WFH to £90k Are you an experienced Backend Software Engineer with strong Python skills and a good knowledge of AI, LLMs and agentic coding? You could be progressing your career at a global finance technology consultancy, working with clients including … using prompt engineering and RAG, optimise and deploy large language and multi-modal models with a focus on performance and latency and build scalable MLOps pipelines and full-stack applications to support robust, production-grade AI deployments. Using a consultative approach you'll guide multidisciplinary teams and clients through strategic ...

capabilities to support real world use cases such as contract and tender analysis * Working within an Azure cloud environment and applying best practices in MLOps and DevOps * Collaborating closely with product teams and senior leadership, including acting as a key partner to the Director of AI Y our Skills … deploying LLM based applications in production environments * Experience working with cloud platforms and modern deployment practices, ideally within Azure * Knowledge of DevOps or MLOps principles * Ability to define architecture and build AI solutions end to end * Strong communication skills and experience working with a range of stakeholders What They Offer ...

accuracy and relevance Optimising and shipping large language and multi-modal models into production, balancing performance, latency, and reliability at enterprise scale Developing robust MLOps pipelines and full-stack applications that underpin scalable, production-ready AI deployments Acting as a trusted advisor to clients and internal teams on GenAI strategy … operating at scale Solid Python engineering skills, with a proven ability to build and ship backend systems and APIs Hands-on knowledge of MLOps, cloud-native infrastructure, and the observability practices that keep AI systems performing in the real world Comfortable leading technical teams and bridging the gap between engineering ...

instrumental in shaping their technological framework from its inception. Model Development: Build advanced molecular property prediction models and expand their AutoML pipelines . Infrastructure & MLOps: Architect the core ML infrastructure, including training pipelines, experiment tracking, model registries , and CI/CD for models. Data Curation: Curate and prepare specialized datasets … production , going beyond simple research prototypes. Experience working specifically with ADMET Data Engineering Excellence: Strong software engineering skills and hands-on experience with MLOps tooling, containerization, and model serving . Cloud Fluency: Highly comfortable with AWS, GCP, or Azure and Infrastructure-as-Code. Communication: Ability to collaborate across disciplines ...

experimentation with A/B and Multi-armed bandit testing frameworks, power analysis, variance reduction, and online-offline alignment.* Work together with Data Engineering, MLOps, and Game Tech teams to guarantee dependable data foundations, feature accessibility, and model deployment pathways.* Build internal data products to improve the speed and quality … problem definition to production deployment and monitoring.* Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics.* Hands-on experience in software engineering, MLOps, and deploying machine learning models at scale.* Proficiency in SQL, Python, and familiarity with big data technologies (e.g., Kafka, Spark) and/or cloud platforms ...

experimentation with A/B and Multi-armed bandit testing frameworks, power analysis, variance reduction, and online-offline alignment. Work together with Data Engineering, MLOps, and Game Tech teams to guarantee dependable data foundations, feature accessibility, and model deployment pathways. Build internal data products to improve the speed and quality … problem definition to production deployment and monitoring. Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics. Hands-on experience in software engineering, MLOps, and deploying machine learning models at scale. Proficiency in SQL, Python, and familiarity with big data technologies (e.g., Kafka, Spark) and/or cloud platforms ...

Senior/Lead Machine Learning Engineer - Time-Series, Pricing, Customer Behaviour, Feature stores, MLOps London Hybrid | £100,000 – £120,000 + Equity This is a genuinely interesting opportunity for someone who enjoys solving large-scale, real-world machine learning problems rather than purely experimental work. The team is building forecasting … hybrid with two days per week onsite in London. Experience around forecasting, time-series modelling, recommendation systems, production ML infrastructure, or large-scale MLOps environments would all be highly relevant. Salary: £100,000 - £120,000 plus equity and benefits. APPLY NOW for immediate consideration. N.B. - They do not offer visa ...

leadership across the full lifecycle of machine learning systems while architecting production-grade ML solutions. You will work with AWS SageMaker, lead teams on MLOps strategies, and ensure systems adhere to governance standards. This is a hands-on, technical position ideal for those with deep expertise in ML frameworks such ...