software development tools and practices (Git version control, code review), and with project management tools (JIRA or similar) in an agile environment. Familiarity with other ML Ops tools (Kubeflow, MLflow, etc.) or big data processing frameworks (Spark) can be an added advantage Rewards and Benefits We believe in supporting our employees in both their professional and personal lives. As part More ❯
and managed AI/ML services. Hands-on experience with Docker, Kubernetes, and container orchestration. Expertise with Databricks, including ML workflows and data pipeline management. Familiarity with tools like MLflow, DVC, Prometheus, and Grafana for versioning and monitoring. Experience implementing security and compliance standards for AI systems. Strong problem-solving and communication skills, with a collaborative mindset. Experience with support More ❯
CD systems, Git workflows, and infrastructure-as-code tooling Hands-on expertise with Azure Databricks and cloud-native technologies (Docker, Kubernetes, Terraform) Solid understanding of MLOps concepts and tooling (MLflow, Airflow etc.); exposure to LLMOps is advantageous Experience working with Generative AI/LLMs, and familiarity with AI engineering agents (e.g., Cursor, Claude Code, Codex) Strong SQL capability and proven More ❯
Skills: Experience using R and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations or regulated industries. Strong working knowledge of Excel More ❯
in production environments serving real users. Strong proficiency in containerisation (Docker, Kubernetes) and orchestration of multi-stage ML workflows. Hands-on experience with ML platforms and tools such as MLflow, Kubeflow, Vertex AI, SageMaker, or similar model management systems. Practical knowledge of infrastructure as code, CI/CD best practices, and cloud platforms (AWS, GCP, or Azure). Experience with More ❯
and act on. Key requirements: MSc or BSc in Computer Science, Data Science, Bioinformatics, Engineering, or a related field, or equivalent experience. Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine learning and More ❯
CSQ426R241 The Forward Deployed AI Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services (PS) engagements to help our customers build and productionize first of its kind AI applications with a More ❯
About Lendable Lendable is on a mission to make consumer finance amazing: faster, cheaper, and friendlier. We're building one of the world's leading fintech companies and are off to a strong start: One of the UK's newest More ❯
