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Senior Machine Learning Engineer
Build and maintain an internal AIOps/ML/LLM platform, including Kubernetes infrastructure, ML workflows, and production deployment for cybersecurity use cases.
#EG Machine Learning Engineer
Design, build, and deploy scalable ML models and pipelines in Python using TensorFlow/PyTorch, integrating them into production systems and monitoring performance.
Senior Hybrid Cloud Architect - (Data Center)
Lead Ford’s hybrid cloud and on-prem infrastructure team, designing scalable systems, migrating legacy datacenters to cloud, and automating deployments with IaC and CI/CD.
Quantitative Software Engineer
Build and maintain mathematical models and backend systems that power financial risk calculations and AI-driven workflows using Python, PySpark, and Databricks.
Data Scientist, Applied AI - Latin America - Remote
Build and productionize generative AI models and LLM-driven applications using PyTorch, RAG pipelines, and vector databases, while engineering robust MLOps and data pipelines in Python.
MLOps & AI Data Engineer — Cloud-Native ML Expert
Build and maintain cloud-native ML pipelines and automation for AI model deployment using tools like MLflow, Kubeflow, and AWS SageMaker.
MLOps Engineer / AI Data Engineer
Build and maintain AI/ML pipelines, deploy models, and manage lifecycle with tools like MLflow, Kubeflow, or cloud platforms (AWS SageMaker/Azure ML).
(Senior) AI Engineer - Data & AI Organisation (all genders)
Build and deploy enterprise-grade AI solutions using LLMs, predictive models, and agentic workflows on AWS, Snowflake, and Palantir Foundry to deliver scalable analytics and insights across Merck’s business functions.
Senior AI Research Engineer
Build and scale AI infrastructure for industrial automation, bridging research and production with MLOps and distributed systems.
FS Technology Consulting - AI and Data - Data Engineer - Senior Consultant - Dublin
Senior Data Engineer builds and optimizes cloud-based data pipelines for financial services clients using Azure, SQL, and ETL tools to enable analytics and reporting.
Applied AI / ML Lead Software Engineer â Employee Platforms
Lead the design and delivery of LLM-powered and agentic AI workflows for JPMorganChase’s internal employee platforms, integrating AI safely into enterprise systems while ensuring reliability and compliance.
Data Scientist
Build and deploy optimisation, forecasting, and scheduling models using Python, SQL, Databricks, and MLflow to improve operational decisions for a client’s AI transformation.
AI/ML Associate Engineer
Build and deploy secure, production-grade AI/ML systems including LLM workflows, RAG pipelines, and agentic AI for enterprise use at a global bank.
Applied AI / ML Lead Software Engineer
Lead the design and delivery of LLM-powered and agentic AI workflows for JPMorgan’s internal employee platforms, integrating secure AI tools and ensuring reliability and compliance.
Data Scientist
Build and deploy large-scale AI solutions for Microsoft’s enterprise customers, using Python/C++ and cloud platforms to analyze data and deliver Responsible AI outcomes.
Data Scientist
Build and fine-tune ML models (regression, forecasting, classification) and LLM applications using Python, Databricks, and Azure AI Foundry; drive insights with PySpark/SQL and champion MLOps with MLflow.
Artificial intelligence engineer (ai engineer) – build ai products in online gaming – cape town[...]
Build and deploy AI products for online gaming, including recommendation engines, LLM apps, and player-assistant agents using Python, AWS, and ML tools.
Senior ai engineer
Senior AI Engineer builds and deploys enterprise AI solutions—LLM apps, RAG, agents, and predictive models—using Python, PyTorch, and cloud platforms to automate and enhance decision-making.
Lead AI Agents & Generative AI Architect
Lead the design and implementation of scalable GenAI, LLM, and AI-agent architectures, including RAG and MLOps/LLMOps pipelines, to deliver enterprise solutions and accelerate client adoption.
Data/ML DevOps Engineer
Build and own the data infrastructure and MLOps tooling for Neurode’s brain-computer interface, turning raw neural signals into pipeline-ready training data at petabyte scale.