22 of 22 MLflow Jobs in London

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 cloud services (AWS, Azure ...

etc.) Experience with LLMs/GenAI frameworks (LangChain, RAG, prompt engineering, etc.) Experience in cloud (AWS/Azure/GCP) Experience in MLOps tools (MLflow, Kubeflow, SageMaker, Azure ML, etc.) API development experience ...

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 in a fast-paced environment Ability to communicate technical ...

experience with core GenAI frameworks (e.g., LangChain, LlamaIndex) and Agentic AI frameworks (e.g., AutoGen, CrewAI, LangGraph). Proficiency in MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Strong working knowledge and practical deployment experience on major cloud platforms (AWS, Azure, GCP), including their AI/ML services. Strong foundation ...

XGBoost, LightGBM, or CatBoost. Experience with model deployment tools (e.g., ONNX, TensorRT, TensorFlow Serving, TorchServe). Familiarity with ML lifecycle tools such as MLflow, Kubeflow, or Azure ML Pipelines. Experience working with distributed data processing (e.g., PySpark) and SQL. Understanding of software engineering best practices, including version control (Git). ...

scalable, maintainable, and production-ready AI systems. Proficiency in Python with AI/ML frameworks (PyTorch, TensorFlow). Experience with MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Deep proficiency in Python and extensive experience with relevant AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK ...

learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures Ability to absorb complex scientific and technical concepts ...

Search, Pinecone/Weaviate/Milvus/pgvector ● Knowledge Graphs - Neo4j, Amazon Neptune, or TigerGraph ● Data Platform - Databricks (Delta Lake, Unity Catalog, Spark SQL, MLflow) ● Embedding models - OpenAI, Cohere, sentence-transformers, BGE ● Re-ranking - Cohere Rerank, cross-encoders, ColBERT ● Document processing - Unstructured.io, LlamaParse, Apache Tika ● LLM providers - OpenAI (GPT-4+ ...

teams and delivering enterprise-grade data solutions. Preferred Qualifications Databricks certifications (e.g., Databricks Certified Data Engineer Professional, Architect ). Experience building ML solutions using MLflow or integrating with cloud ML services. Experience in BFSI, Retail, Telecom, or Healthcare data environments. Experience with real-time data processing (Kafka, EventHub, Kinesis). ...

building simple data pipelines or transformation workflows is a plus. Exposure to ML Ops or production systems (nice to have) Familiarity with tools like MLflow, Weights & Biases, or cloud platforms (Azure, AWS, or GCP). Experience deploying models via APIs or lightweight services is a bonus, not a requirement. Software ...

frameworks like PyTorch, TensorFlow, or scikit-learn Hands-on experience with LLMs (prompting, RAG, fine-tuning, agents) Understanding of MLOps principles and tools (e.g. MLflow, DVC, Weights & Biases) Experience deploying solutions in AWS or cloud environments Familiarity with Docker, CI/CD, and version control (Git) Ability to translate complex ...

models into production using modern cloud platforms (AWS/Azure/GCP). Build scalable APIs, inference pipelines, and end‐to‐end MLOps workflows (MLflow, Kubeflow, Azure ML, Vertex AI, etc.). Shape the future of our AI platform Prototype bold new ideas fast. Iterate with a “learn quickly, ship ...

Hugging Face ecosystem Experience with audio or speech models and frameworks. Experience building and maintaining end-to-end ML pipelines and MLOps tooling (e.g. MLflow, Weights & Biases, DVC, or similar). Strong Python skills; experience with Docker, CI/CD, and cloud platforms (Azure preferred) Practical experience designing agentic ...

technical fluency across modern data and AI stacks including cloud-native architectures (Azure, AWS), data platforms (Databricks, Snowflake, Microsoft Fabric), ML/AI tools (MLflow, LLMs, RAG pipelines, vector stores) and analytics technologies (Power BI, Tableau) Experience reviewing end-to-end data programmes and defining future-state delivery models ...

series. Experience building LLM solutions (prompting, retrieval, agent flows; LangGraph, MCP) and integrating with trading data/services. Experience with CI/CD, Terraform, MLflow/feature stores, vector DBs, and governance (PII handling, data lineage). Excellent stakeholder skills; able to work on‐desk with traders/analysts ...

Python (expert), C++ for inference (strong — Android NDK), Swift and Kotlin awareness (basic — enough to understand integration surface), Git/CI/CD, Docker, MLflow/W&B. Required Skills Expertise in machine learning frameworks, computer vision, signal processing, model optimisation, and programming languages as detailed above. Preferred Skills Experience ...

including Circadia’s clinical monitoring hardware, working with firmware and embedded engineering teams as needed. Manage model versioning, promotion, and rollback workflows through the MLflow model registry. Evaluate and implement strategies for safe model rollouts (e.g. shadow deployments, canary releases) as the platform matures. Experiment Tracking & Model Registry Maintain … improve the MLflow-based experiment tracking and model registry infrastructure. Establish conventions for experiment logging, artifact storage, model metadata, and lineage tracking. Enable ML engineers to move seamlessly from experimentation to production deployment with minimal friction. Data & Model Versioning Implement and maintain training data versioning and dataset management practices ...

Senior ML/MLOps Engineer (MLflow) | Databricks | Azure) About Optima Partners We’re an advanced data & business consultancy helping major consumer brands transform through data-driven customer strategy, design, and engineering. Our clients include leading UK and global brands across financial services, retail, and more. Join a practitioner-led, fast … loves building real, production grade ML systems not just proof‐of‐concepts. If you enjoy working across the full ML lifecycle and have strong MLflow experience, this role is built for you. What You’ll Do Own end-to-end ML model lifecycles from training to deployment to monitoring Productionise ...

models. The focus of the role is building and enabling production-grade ML environments rather than model development itself. Candidates must have deep MLflow experience and proven delivery in real-world client settings. Key Responsibilities Design, build, and maintain end-to-end MLOps environments to support model training, tracking, deployment … monitoring Implement MLflow for: Experiment tracking; Model registry; Model versioning and lifecycle management Enable model deployment into production (batch and/or real-time) with robust CI/CD Work closely with Data Scientists to transition models from experimentation to production Build scalable, secure, and reproducible ML platforms Establish best ...

3. Staff SE – MLOps/DevOps for AI Shaping the infrastructure behind model serving, training pipelines, LLMOps, and AgentOps across the full AI stack. ▸ MLFlow · Databricks · Datadog · Terraform ────────────────────────── What all three roles require: • 7+ years in AI/ML engineering, shipping models in production • 3+ years in a Staff-level … collaborative leadership style — mentoring engineers, shaping best practices ────────────────────────── Core stack: Python · Rust · Java · Amazon Bedrock · SageMaker · Vertex AI · LangGraph · Pydantic AI · LangFuse · MLFlow · Databricks · Datadog · Claude Code · Docker · K8s · Terraform · Vector DBs · Graph DBs ────────────────────────── London hybrid (2 days/week) Competitive Salary and benefits Not eligible for visa sponsorship ────────────────────────── Interested ...

turn ideas into impactful solutions. Optimize and deploy models with tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT. Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale data using PySpark and integrate ML solutions into production environments. Monitor and improve model performance … LightGBM, CatBoost, TensorFlow, Keras, PyTorch). Familiarity with model deployment and serving tools (ONNX, TensorRT, TensorFlow Serving, TorchServe). Experience with ML lifecycle tools (MLflow, Kubeflow, Azure ML Pipelines). Knowledge of distributed data processing (PySpark) and software engineering principles (Git). A collaborative mindset and excellent problem-solving abilities. ...

Lead Data and AI Architect Salary 40,000 - 45,000 AED per month + medical, visa, and life insurance Location: Dubai (DIFC Innovation Hub) Discover the opportunity We are seeking an energetic Lead Data and ...