with internal policies and external regulations. Provide technical input on risk mitigation strategies and onboarding documentation. Security & DevSecOps Integration Integrate AI security controls into CI/CD pipelines and MLOps workflows. Use tools such as Azure Key Vault, Microsoft Entra ID, and GitHub Actions for secure deployment and access management. Monitor AI systems using Azure Monitor, Log Analytics, and Application More ❯
frameworks such as PyTorch or TensorFlow Familiarity with FDA regulatory pathways for medical software (e.g., 510(k), De Novo), and standards like IEC 62304 or ISO 13485 Experience with MLOps practices and model versioning in compliant environments Preferred Qualifications: Experience building ML models with wearable data (e.g., continuous heart rate, motion, respiration) Exposure to embedded AI or edge model deployment More ❯
and toolchains Experienced in and strong knowledge of using AI/ML and more particularly LLMs eager to apply this rapidly changing technology Experience with CI/CD and MLOps tools/frameworks (e.g. MLflow and W&B) Experienced in building and running a large platform at scale Strong distributed systems skills and knowledge Strong system architecture skills Knowledge of More ❯
NoSQL/graph databases. Extensive experience with ML & DLplatforms,frameworks, and libraries. Extensive experience with end-to-endmodel design and deploymentwithin cloud environments. Asystems thinking approach, with passion for MLOps best practises. An engineer that can think in O(n) as much as plan the orchestration of their product. Solid understanding of data structures,data modelling, and software architecture, especially More ❯
NoSQL/graph databases. Extensive experience with ML & DLplatforms,frameworks, and libraries. Extensive experience with end-to-endmodel design and deploymentwithin cloud environments. Asystems thinking approach, with passion for MLOps best practises. An engineer that can think in O(n) as much as plan the orchestration of their product. Solid understanding of data structures,data modelling, and software architecture, especially More ❯
documents, index embeddings (Pinecone, FAISS, Weaviate), and build similarity search features. Rapid Prototyping: Create interactive AI demos and proofs-of-concept with Streamlit, Gradio, or Next.js for stakeholder feedback; MLOps & Deployment: Implement CI/CD pipelines (e.g., GitLab Actions, Apache Airflow), experiment tracking (MLflow), and model monitoring for reliable production workflows; Cross-Functional Collaboration: Participate in code reviews, architectural discussions 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 … Learning Engineering Manager - Personalization London, England, United Kingdom 6 days ago London, England, United Kingdom 1 day ago London, England, United Kingdom 1 day ago Machine Learning Engineering Manager - MLOps London, England, United Kingdom 6 days ago Manager, Lead Research Scientist, Training Data (Foundational Research) London, England, United Kingdom 6 days ago Quantitative Researcher: Europe Tactic Specialist - Two Sigma Securities More ❯
Proven ability to design and deploy full-stack AI pipelines in production Strong experience in backend engineering , ideally with Go and ML frameworks like PyTorch or TensorFlow Familiarity with MLOps , cloud infrastructure (AWS) , Kubernetes , and Terraform Experience evaluating and deploying models (including anomaly detection, RAG, and clustering) in noisy, evolving data environments Nice to Have: Experience with Perl Knowledge of More ❯
knowledge as a plus. Demonstrated experience building APIs supporting analytics, research, or actuarial functions in an insurance environment. Proficiency with cloud technologies such as Snowflake, Databricks, and familiarity with MLOps frameworks. Exhibit strong collaboration, problem-solving, and communication skills, with the ability to adapt to changing priorities and simplify complex problems. More ❯
knowledge as a plus. Demonstrated experience building APIs supporting analytics, research, or actuarial functions in an insurance environment. Proficiency with cloud technologies such as Snowflake, Databricks, and familiarity with MLOps frameworks. Exhibit strong collaboration, problem-solving, and communication skills, with the ability to adapt to changing priorities and simplify complex problems. More ❯
in cloud platforms such as Google Cloud. Expertise in statistical techniques such as GLMs, classification, survival models, forecasting, and optimisation. Hands-on experience with experimentation and causal inference. Strong MLOps knowledge and experience deploying models into production environments using CI/CD. Experience with data visualisation tools like Tableau, and communicating to both technical and non-technical audiences. If this More ❯
in cloud platforms such as Google Cloud. Expertise in statistical techniques such as GLMs, classification, survival models, forecasting, and optimisation. Hands-on experience with experimentation and causal inference. Strong MLOps knowledge and experience deploying models into production environments using CI/CD. Experience with data visualisation tools like Tableau, and communicating to both technical and non-technical audiences. If this More ❯
AI Engineer include: Strong Data Science Foundations – bring solid grounding in statistics and machine learning, along with strong programming skills – Python preferred. Bonus points if you have exposure to MLOps tools and workflows. Passion for Cutting-Edge AI – You actively experiment with and apply modern AI technologies such as LLMs, RAGs, co-pilots, agentic workflows, and more. You’re always More ❯
AI Engineer include: Strong Data Science Foundations – bring solid grounding in statistics and machine learning, along with strong programming skills – Python preferred. Bonus points if you have exposure to MLOps tools and workflows. Passion for Cutting-Edge AI – You actively experiment with and apply modern AI technologies such as LLMs, RAGs, co-pilots, agentic workflows, and more. You’re always More ❯
adoption within client environments, including training, stakeholder enablement, and operational integration. Technical Mentorship: Mentor and guide technical teams (data scientists, engineers) in best practices for advanced AI development, deployment, MLOps/LLMOps, and agentic system design. Stakeholder Management: Build and maintain strong relationships with key internal and external stakeholders, effectively communicating complex technical concepts and project progress. Innovation & IP Development … AI systems. Cloud Platforms: Strong working knowledge and practical deployment experience on at least one major cloud platform (AWS, Azure, GCP), including their AI/ML services. LLMOps/MLOps: Expertise in designing and implementing robust MLOps/LLMOps pipelines for automated testing, CI/CD, monitoring, and governance of complex AI models and applications. Leadership & Communication: Proven ability to More ❯
Join our team as an MLOps Engineer who acts as the critical bridge between Data Scientists and DevOps Engineers. Translate experimental ML models into scalable, production-ready applications using cutting-edge AWS services. The Role Core Responsibilities: Technical Liaison - Bridge Data Science and DevOps teams, ensuring effective AI/ML solution deployment Hands-On Support - Assist data scientists with DevOps … issues, Docker containers, and MLOps tooling Model Deployment - Deploy Hugging Face Transformers and ML models as secure microservices AWS ML Platform - Build and evaluate models using SageMaker, Bedrock, Glue, Athena, and Redshift Knowledge Transfer - Create documentation and mentor teams on MLOps best practices Full ML Lifecycle - Manage training, validation, versioning, deployment, monitoring, and governance API Development - Develop secure APIs using … Cloud architecture - Working across cloud-based infrastructures Tech Stack & Tools AWS Services: SageMaker, Bedrock, Glue, ECS Fargate, Athena, Kendra, RDS, Redshift, Lambda, CloudWatch Development: Python, R, Flask, FastAPI, SQL MLOps: Apigee, Hugging Face, Jenkins, Git, Docker Environments: Jupyter, RStudio, Linux What We're Looking For Experience Level: Sr. Associate or Manager with hands-on data analytics and software delivery experience More ❯
model optimization (i.e. quantization, pruning) and model deployment frameworks such as TensorRT, ONNX Runtime, and OpenVINO. Proficiency with CUDA programming and optimizing code for GPU acceleration. Strong background in MLOps practices, including CI/CD using GitHub Actions and containerization with Docker. Excellent problem-solving skills and the ability to thrive in a fast-paced, high-intensity environment. Experience contributing More ❯
model optimization (i.e. quantization, pruning) and model deployment frameworks such as TensorRT, ONNX Runtime, and OpenVINO. Proficiency with CUDA programming and optimizing code for GPU acceleration. Strong background in MLOps practices, including CI/CD using GitHub Actions and containerization with Docker. Excellent problem-solving skills and the ability to thrive in a fast-paced, high-intensity environment. Experience contributing More ❯
and deploying object detection models, particularly within the YOLO family. Familiarity with model optimization techniques such as quantization and pruning, and deployment frameworks like TensorRT and OpenVINO. Experience with MLOps tools and practices, including version control (Git), Docker, and CI/CD with GitHub Actions. Excellent problem-solving skills and the ability to perform in a fast-paced, high-intensity More ❯
and deploying object detection models, particularly within the YOLO family. Familiarity with model optimization techniques such as quantization and pruning, and deployment frameworks like TensorRT and OpenVINO. Experience with MLOps tools and practices, including version control (Git), Docker, and CI/CD with GitHub Actions. Excellent problem-solving skills and the ability to perform in a fast-paced, high-intensity More ❯
Python and SQL (BI tools such as SuperSet, Tableau or PowerBI is a bonus) Hands-on experience in machine learning model development, evaluation, and production deployment, with familiarity in MLOps principles to build scalable and standardised workflows and implement effective ML monitoring systems Proven ability to create polished presentations and effectively communicate insights to customers with attention to detail Have More ❯
Python and SQL (BI tools such as SuperSet, Tableau or PowerBI is a bonus) Hands-on experience in machine learning model development, evaluation, and production deployment, with familiarity in MLOps principles to build scalable and standardised workflows and implement effective ML monitoring systems Proven ability to create polished presentations and effectively communicate insights to customers with attention to detail Have More ❯
Python and SQL (BI tools such as SuperSet, Tableau or PowerBI is a bonus) Hands-on experience in machine learning model development, evaluation, and production deployment, with familiarity in MLOps principles to build scalable and standardised workflows and implement effective ML monitoring systems Proven ability to create polished presentations and effectively communicate insights to customers with attention to detail Have More ❯
next generation of automotive software development. The right candidate will have excellent communication skills, solid coding skills, broad knowledge of software development across areas such as Cloud, Compute Frameworks, MLOps, Observability and Build Infra. RESPONSIBILITIES: Work on high-impact projects and innovate new solutions to problems in the self-driving space Work with Computer Vision and Machine Learning engineers on More ❯
a related field Experience with multi-modal models that combine vision and language Strong grasp of data-centric AI practices - annotation tooling, prompt evaluation, and dataset curation Familiarity with MLOps tools (e.g. Weights & Biases, SageMaker, MLflow) Experience working in regulated sectors like insurance, banking, or property What You'll Be Doing This is a hands-on, high-impact role - you More ❯
