1 to 25 of 40 Remote/Hybrid MLOps Jobs in London

learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: Competitive Salary & Bonus : £35,000 – £45,000 plus bonus Hybrid Working : A flexible mix of office ...

every model we build is fair, free from bias, and explainable to consumers, customers, and regulators. Engineering & Deployment: Work within the engineering team on MLOps to containerise, deploy, and monitor models in high-scale production. Skills & Requirements Core Data Science: Foundational Stats: You must have an excellent grasp of Linear ...

fast-paced environment Nice to Have Experience within financial services or other regulated industries Exposure to vector databases (e.g. Pinecone, Weaviate, FAISS) Experience with MLOps/LLMOps and deploying models into production Familiarity with LLM fine-tuning, evaluation, or guardrailing techniques Experience building internal tools such as copilots or knowledge ...

Solid understanding of ETL and data engineering best practices Experience with SQL/NoSQL, APIs, and cloud platforms Familiarity with big data tools and MLOps concepts Strong communication, collaboration, and mentoring skills Main Tech Stack: Python AWS (S3, Athena), Terraform, Docker Prefect, Pulsar PostgreSQL, Cassandra GitLab CI/CD What ...

systems . Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment. Optimise model performance, scalability, and reliability using MLOps best practices. Work with large-scale structured and unstructured datasets for model training and validation. Implement model monitoring, versioning, and retraining processes to ensure continuous … TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with ...

product-focused mindset, balancing experimentation with real-world value. Useful additional experience includes: AWS or GCP environments (SageMaker, Bedrock, Lambda, S3, Redshift). MLOps practices (monitoring, deployment, optimisation). Working with streaming data, transformer models or recommendation systems. What They Offer £70,000 to £90,000 salary. Hybrid working with ...

frameworks, including embeddings, prompt engineering, or fine tuning Experience building end to end ML pipelines, including model validation, optimisation, deployment, and monitoring Understanding of MLOps practices, including model versioning, model registries, CI/CD for ML, and automated training/inference workflows Ability to translate business problems into analytical tasks ...

deal requirements into technical solutions. Support post‐merger integration (PMI) through AI‐enabled insights, reporting, and performance tracking. Deploy solutions into production using modern MLOps and cloud practices . Ensure models are explainable, auditable, and aligned with governance and regulatory requirements in transaction contexts. Contribute to AI strategy, architecture … Spark, Airflow or similar) LLMs, NLP, and document intelligence (e.g. RAG, embeddings) Experience with cloud platforms (AWS, Azure, or GCP). Understanding of MLOps , CI/CD, model monitoring, and governance. M&A/Transaction Experience Direct experience supporting M&A, private equity, corporate development, or transaction advisory . Proven ...

operate and maintain AI development and production environments using Azure services, including AI, ML and GenAI workloads. Design and manage CI/CD and MLOps pipelines to support model development, deployment, monitoring and lifecycle management. Provision and secure cloud environments using Infrastructure as Code, with a strong focus on automation ...

Searches: ML Engineer/AI Engineer/Cloud Engineer/Machine Learning/Cloud AI/Google Cloud/GCP/Vertex AI/MLOps/ML Ops/AIOPs/AI Ops/ ...

related field Experience with genomics pipelines or tools (e.g. FASTQ, BAM, variant calling) Knowledge of protein structure modelling or drug discovery workflows Exposure to MLOps, deployment, and production systems Publications or open-source contributions in relevant domains Why Join Them Opportunity to work on genuinely impactful problems in healthcare ...

experience in training and deploying computer vision models into production · Proven track record with LLM fine-tuning, prompt engineering and productionisation · Deep experience in MLOps on Azure, including CI/CD, monitoring and scaling pipelines. · Strong coding skills in Python, with frameworks such as PyTorch, FastAPI and Azure CLI. ...

working in cloud environments, ideally Azure. Solid understanding of software engineering fundamentals including APIs, distributed systems and secure system design. Experience with DevOps or MLOps practices such as CI CD, containerisation and monitoring. The confidence and gravitas to influence technical direction and guide a less mature AI function. A practical ...

coaches, analysts, and execs Highly Desirable Skills Football Analytics Experience : Familiarity with football-specific datasets (event, tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming ...

systems tailored to audit applications. Contribute to architectural decisions and solution governance. Write clean, efficient, and scalable code that adheres to software engineering principles, MLOps practices, and cloud-native development. AI Solution Delivery: Own the implementation of ML pipelines, APIs, and data integration workflows. Operational Excellence: Contribute to defining reusable … development patterns, enforcing coding standards, and implementing MLOps best practices that support version control, performance optimisation, and maintainability. Cross-Disciplinary Collaboration: Work side-by-side with data scientists, product managers, platform engineers, and QA teams to align on technical requirements, delivery timelines, and integration plans. Provide hands-on contributions ...

traditional ML solutions end-to-end Comfortable in startup or scale-up environments — fast-moving, iterative, delivery-focused Strong Python engineering experience Experience with MLOps, CI/CD, IaC, and productionising ML models Ability to work collaboratively with product, data, and engineering teams Contract Details Location: Hybrid London ...

authentication/security best practices. A disciplined engineering mindset — you think about reliability, maintainability, and long-term scalability. Nice-to-haves Experience with MLOps and model-serving infrastructure. Background in high-performance computing or large-scale scientific workloads. Expertise in data pipeline architecture and real-time streaming systems. Knowledge ...

team environment Nice to Have Background in bioinformatics, computational biology, or life sciences Experience with drug discovery, protein modelling, or genomics pipelines Familiarity with MLOps, CI/CD, and scalable cloud infrastructure Exposure to graph-based models, transformers, or multimodal learning Experience in an early-stage startup or fast-scaling ...

your own on architectural trade-offs. You're fluent enough in the modern data and AI stack - Python, cloud-native services, event-driven architectures, MLOps tooling, LLM evaluation - to make informed product calls without relying on engineering to tell you what's possible. Salary and equity calibrated to the seed ...

iteration. Hands-on experience scaling a modern cloud data platform (lake/warehouse, orchestration, streaming). Deep understanding of the full ML lifecycle and MLOps/analytics engineering best practices. Experience implementing data architecture standards, data contracts, and governance across domains. Leadership experience managing managers and senior ICs within growing ...

PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research in machine learning are also beneficial. At a personal level we’re also looking for someone who is: Passionate about delivering software ...

inference performance via batching, quantisation, distillation, LoRA/PEFT, accelerator utilisation (GPU/TPU), and efficient memory/latency tuning Build and maintain MLOps/LLMOps workflows-CI/CD for models and prompts, model registry/versioning, feature stores, and automated promotion across environments Instrument observability for data, models … Gateways and ISTIO, ability to Diagnose and intercept failures in End to End communication Implement best practices for data governance, security, and MLOps on GCP Proficiency with Python and common AI/ML frameworks such as TensorFlow, PyTorch, JAX, scikit learn, and Hugging Face libraries Knowledge of MLOps and LLMOps ...

work from home. The AI Engineer will support delivery of AI use cases, workflows, analytics and solutions - responsible for tasks such as pattern recognition, MLOps, software development, neural networks, and natural language processing on a day-to-day basis. Qualifications Pattern Recognition and Neural Networks skills Computer Science and Software ...

across the end-to-end delivery of machine learning systems. This includes building models, running experiments, and deploying scalable solutions using modern cloud and MLOps tooling. Key Responsibilities Include: Designing and developing machine learning models (e.g. classification, forecasting, anomaly detection) Supporting experimentation cycles: hypothesis definition, testing, and evaluation Contributing … PyTorch, TensorFlow, or XGBoost Exposure to AWS services (e.g. S3, Lambda, SageMaker) Understanding of core ML concepts: model evaluation, validation, and experimentation Familiarity with MLOps or experiment tracking tools (e.g. MLflow, Weights & Biases) Awareness of LLMs or generative AI concepts Strong problem-solving ability and willingness to learn ...

development Solid understanding of anomaly detection techniques Experience building data workflows/pipelines Desirable: Experience working in secure/government environments Knowledge of MLOps best practices Familiarity with real-time or near real-time data processing Contract Details: Location: London (hybrid) Duration: 6 months Day Rate: Up to £595/ ...