LLMs) and prompt engineering (e.g., GPT, BERT, T5 family). Familiarity with on-device or edge-AI deployments (e.g., TensorFlow Lite, ONNX, mobile/embedded inference). Knowledge of MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) for experiment tracking and model governance. Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL More ❯
GPT4 Omni, Qwen-vl, DocOwl etc.) for understanding complex documents and images. Experience in training, evaluating and hosting open source LLMs would be a major benefit. Some experience with MLOps would be very beneficial Full-stack development experience Experience with UI technologies like React would be helpful Experience with building search applications using Azure Search, Sinequa, Elastic or anything Lucene More ❯
to medium sized machine learning projects in small cross functional squads. What wed like to see from you: Strong understanding of a wide range of ML algorithms. Understanding of MLOps practices for managing and monitoring models in production. Experience with deep learning frameworks (e.g. TensorFlow, PyTorch). Proficiency in programming languages such as Python, SQL and R. Knowledge of SQL More ❯
Proficiency in Python and SQL. Experience with big data technologies like Apache Hadoop and Apache Spark. Familiarity with real-time data processing frameworks such as Apache Kafka or Flink. MLOps & Deployment: Experience deploying and maintaining large-scale ML inference pipelines into production environments. Proficiency with Docker for containerization and Kubernetes for orchestration. Familiarity with AWS cloud platform (experience with GCP More ❯
SQL, BigQuery, noSQL) to programming languages (e.g. R, Python), and from data visualisation (e.g. Tableau, PowerBI) to machine learning. Understanding data engineering solutions is a plus. Strong experience in MLOps, including model lifecycle management, CI/CD for ML, monitoring, and scalable deployment of ML pipelines in production environments Knowledge of CloudOps practices, with expertise in managing scalable, cost-optimized More ❯
Lancaster, Lancashire, United Kingdom Hybrid / WFH Options
Galaxy Systems
Bedrock, etc.). Desired: Experience deploying models as APIs/microservices in cloud-native environments. Familiarity with prompt tuning, embedding generation, vector search, and knowledge retrieval frameworks. Understanding of MLOps best practices, version control, CI/CD pipelines, and containerization (Docker, Kubernetes). Prior experience working with GenAI tools and response-augmented generation workflows. Education: Bachelor's or Master's More ❯
and other related methods. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc. Experience working with large-scale MLOps pipelines, working with and deploying models to production services. About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most More ❯
problem Experience with experiment design and conducting A/B tests Proficiency in Python, with the ability to write production-grade code and a good understanding of data engineering & MLOps Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch Collaborative and humble great teammate with an ability to work wimulti More ❯
Ability to design, deploy and maintain ML solutions on modern frameworks to meet functional business requirements, adhering to software engineering best practices and with exposure to version control, testing, MLOps, CI/CD and API design Hands on experience in using one of 3 major cloud technologies (AWS, Azure or GCP) in a production environment, as well as ML platforms More ❯
on large-scale time-series datasets to improve model accuracy and stability Collaborate with Data Scientists and DevOps to build end-to-end ML pipelines Contribute to model governance, MLOps, and performance monitoring frameworks Participate in code reviews, design discussions, and performance tuning Requirements: 3+ years of experience in a Machine Learning Engineer or similar role Proficiency in Python , ML More ❯
and generative AI systems. Experience with data engineering or analytics platforms. Understanding of AI safety, security, and compliance best practices in production. Enthusiasm for learning and adopting the latest MLOps and AI technologies. #ICB #ICBEngineering About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy More ❯
delivery , balancing innovation with maintainability, scalability, and performance. Develop and maintain reusable components , APIs, and services that enable rapid deployment of AI features across products. Champion best practices in MLOps and software engineering , including CI/CD, testing, observability, and versioning for AI systems. Mentor and guide junior engineers and cross-functional team members, fostering a culture of technical excellence More ❯
problem Experience with experiment design and conducting A/B tests Proficiency in Python, with the ability to write production-grade code and a good understanding of data engineering & MLOps Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch Collaborative and humble great teammate with an ability to work wimulti More ❯
Whetstone, Greater London, UK Hybrid / WFH Options
Etsy
problem Experience with experiment design and conducting A/B tests Proficiency in Python, with the ability to write production-grade code and a good understanding of data engineering & MLOps Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch Collaborative and humble great teammate with an ability to work wimulti More ❯
About Prima Mente Prima Mente's goal is to deeply understand the brain, to protect the brain from neurological disease and enhance the brain in health. We do this by generating our own data, building brain foundation models, and translating More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Method Resourcing
real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data tools (Spark, etc.). Strong written and verbal communication skills, especially More ❯
Mistral. Model performance and optimization: Fine-tuning and optimizing LLMs for quality, latency, sustainability, and cost. Programming and NLP tools: Advanced Python, frameworks like PyTorch, TensorFlow, Hugging Face, LangChain. MLOps and deployment: Docker, Kubernetes, Azure ML Studio, MLFlow. Cloud and AI infrastructure: Experience with Azure Cloud for scalable deployment. Databases and data platforms: SQL, NoSQL, Snowflake, Databricks. OUR VALUES: CURIOSITY More ❯
environment. 3+ years of experience writing production-level code: Routine use and deep understanding of the best practices with version control, unit testing, CI/CD and in general, MLOps for model lifecycle management and monitoring. Familiarity with containerization (Docker) and orchestration for scalable deployment. Ability to write re-usable code What will be your key responsibilities? Plan and lead More ❯
environment. 3+ years of experience writing production-level code: Routine use and deep understanding of the best practices with version control, unit testing, CI/CD and in general, MLOps for model lifecycle management and monitoring. Familiarity with containerization (Docker) and orchestration for scalable deployment. Ability to write re-usable code What will be your key responsibilities? Plan and lead More ❯
environment. 3+ years of experience writing production-level code: Routine use and deep understanding of the best practices with version control, unit testing, CI/CD and in general, MLOps for model lifecycle management and monitoring. Familiarity with containerization (Docker) and orchestration for scalable deployment. Ability to write re-usable code What will be your key responsibilities? Plan and lead More ❯
environment. 3+ years of experience writing production-level code: Routine use and deep understanding of the best practices with version control, unit testing, CI/CD and in general, MLOps for model lifecycle management and monitoring. Familiarity with containerization (Docker) and orchestration for scalable deployment. Ability to write re-usable code What will be your key responsibilities? Plan and lead More ❯
south west london, south east england, united kingdom
Mars
environment. 3+ years of experience writing production-level code: Routine use and deep understanding of the best practices with version control, unit testing, CI/CD and in general, MLOps for model lifecycle management and monitoring. Familiarity with containerization (Docker) and orchestration for scalable deployment. Ability to write re-usable code What will be your key responsibilities? Plan and lead More ❯
Microsoft Azure AI services. Strong understanding of large language models, prompt engineering, and fine-tuning techniques. Experience with data manipulation libraries (e.g., Pandas, NumPy) and cloud platforms. Familiarity with MLOps, version control (e.g., Git), and deployment tools (e.g., Docker, Kubernetes). Excellent problem-solving skills and the ability to work on complex AI challenges. Nice to Have: Experience with NLP More ❯
