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Data Scientist (Platform Development)
Build and maintain data pipelines and ML models for a stealth biotech startup, focusing on signal processing and time-series analysis to drive research insights.
Platform Engineer: Time-Series Data &Automation
Builds scalable data pipelines and time-series analytics using TDengine, Python, and ETL/ELT to enable predictive maintenance and operational reporting for clients.
Machine Learning Engineer / Data Scientist (Mid-Level)
Build, train, and deploy ML models in Python using TensorFlow/PyTorch to solve business problems and maintain production systems.
Data Engineer
Build and maintain Python-based data pipelines in Prefect to ingest API and telemetry data into PostgreSQL, automate reporting, and improve the energy-infrastructure data platform.
Junior Data Engineer
Build and maintain data pipelines, automate integrations, and help scale a cloud data warehouse for a grid-scale energy storage company using Python, SQL, and cloud services.
DevOps Specialist ( REMOTE)
Build and deploy cloud-native apps on Azure, automate CI/CD pipelines, and manage data lakes for real-time analytics and energy-trading workflows.
Full-Stack Data Engineer
Build and maintain cloud-based data pipelines and APIs to process real-time energy data from smart meters and IoT devices, using Scala, Python, and Databricks.
Senior Full-Stack Engineer
Build enterprise-grade React/TypeScript apps and FastAPI backends to help energy markets optimize electricity usage and integrate renewables.
Associate Sales Engineer
Build demos, integrations, and scripts for InfluxDB’s time-series platform, partnering with sales teams to help customers collect, store, and analyze real-time data.
Backend Developer (C++ / Python / Node.js)
Builds scalable backend services in C++, Node.js, or Python for global clients, focusing on high-performance, event-driven systems and cloud-native deployment.
Data Science Engineer for PDA (Photonics), IME
Build automated test systems and data pipelines for silicon photonic devices using Python, instrument control, and ML to analyze optical measurements and optimize chip performance.
Full Stack Engineer
Builds full-stack features for intelligent data-center platforms using Python (FastAPI/Django), React/Next.js, and cloud-native tools, while integrating AI coding assistants into daily workflows.
Senior Backend Developer for NATO with security clearance
Build and operate cloud-based backend services for maritime geospatial analytics using Python, FastAPI, Neo4j, and Databricks, with a focus on secure, scalable microservices and data pipelines.
Data Engineer
Designs and maintains cloud data pipelines and analytics platforms for food and beverage processing plants, integrating industrial IoT data with Azure, Databricks, and InfluxDB to enable predictive maintenance and AI-driven analytics.
FS Technology Consulting - AI and Data - Forward Deployed AI Engineer - Manager - Dublin
Lead AI engineering and architecture for financial-services clients, designing GenAI and multi-agent systems, deploying RAG pipelines, and aligning solutions with EU regulations and enterprise standards.
Full Stack Engineer
Build real-time web trading tools using React, TypeScript, Java, REST APIs and WebSockets in a fast-paced fintech environment.
(1710) Data Engineer - BSTD
Build and maintain scalable data pipelines for the South African Reserve Bank, enabling Data as a Service and advanced analytics using Python, Spark, and cloud platforms.
全栈工程师（Full Stack Engineer）
Build and maintain the FinFAST platform’s full-stack features, integrating LLM APIs for an AI research assistant and creating interactive dashboards to visualize economic data.
Senior Staff Data Engineer
Designs and builds petabyte-scale data pipelines to ingest, transform, and prepare heterogeneous biological datasets (genomics, imaging, metadata) for AI model training, ensuring scalability, reliability, and scientific accuracy to accelerate disease research.
Architect - Machine Learning and Data
Design and lead production ML and generative AI platforms on Microsoft Azure and Fabric, defining MLOps, LLMOps, and enterprise-scale AI architectures for client organizations.