7 of 7 Remote/Hybrid MLOps Jobs in the South West

technical challenges Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical discipline Bonus Skills/Experience Understanding of MLOps, model serving, scaling and monitoring workflows (e.g., BentoML, MLflow, Vertex AI, AWS Sagemaker) Experience building streaming + batch data ingestion and transformation pipelines (Spark/ ...

internal stakeholders Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment Experience of appropriate version control and environment management (such as venvs or Docker) Experience of writing technical project proposals ...

automation Containerisation and orchestration Monitoring and observability tools Experience in the defence or advanced technology sector Experience with GPU based computer environments Experience with MLOps and associated tooling Experience with data pipelines Experience with Infrastructure as Code Experience with security integration in DevOps i.e. DevSecOps Service-oriented with effective communication ...

Architect secure, scalable GenAI solutions on AWS and GCP Build APIs, services, and pipelines to integrate GenAI into real business workflows Apply LLMOps/MLOps practices : versioning, monitoring, cost control, bias, and drift management Work directly with clients to translate business problems into deployable AI solutions , not slide decks Contribute ...

concept to production Establish AI operating models, best practices, and responsible AI frameworks Build and lead high-performing multidisciplinary teams (Data Science, ML Engineering, MLOps) Identify use cases across functions (customer experience, operations, knowledge management, automation) Ensure scalability, security, and compliance of AI platforms Required Experience Proven leadership delivering Generative … deep learning, model optimisation Evaluation frameworks and guardrails Data & Platforms Vector databases (Pinecone, Weaviate, FAISS, Milvus) Knowledge graphs and semantic search Data engineering pipelines MLOps & Deployment CI/CD for ML, model monitoring, versioning Kubernetes, Docker, serverless architectures MLflow, Kubeflow, SageMaker or similar Cloud & Architecture Azure AI, AWS AI/ ...

cloud computing (ideally AWS) Strong experience across industries in both Geospatial and non-Geospatial domains Experience with Machine Learning (sci-kit learn, tensorflow, metaflow, MLOps) Preferred Experience: Experience with frameworks like Metaflow, Prefect, etc. Experience with geospatial libraries i.e. Raster, Geo-pandas, Vector databases Bright Purple is an equal opportunities ...

across both software development and infrastructure. You'll enjoy solving complex technical challenges, working in dynamic environments, and collaborating closely with Data Scientists and MLOps teams. A pragmatic, adaptable mindset is key, along with a passion for building scalable, secure systems that enable data-driven outcomes. You should also … data management initiatives Develop, test and deploy new platform capabilities Troubleshoot and enhance existing analytics services Provide hands-on support to Data Scientists and MLOps teams Tackle complex engineering challenges across a varied tech stack Requirements: Strong experience with Python Experience with Kubernetes and Docker Understanding of CI/ ...