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Applied AI Engineer - (ML / AI / AGI)
Designs and builds production-ready AI services for ranking, summarization, retrieval, and agentic workflows using Python, AWS, and Databricks.
AI/ML Engineer (Computer Vision) | Hybrid Work Setup
Build and deploy AI models, especially computer vision, to extract consumer insights and drive retail decisions using Python, PyTorch, and Azure ML.
Machine Learning Engineer
Build and deploy ML/AI systems for manufacturing—computer vision, predictive analytics, and anomaly detection—to improve quality and automation in plant operations.
Generative AI Architect (Databricks & Agentic AI)
Design and govern end-to-end enterprise GenAI architectures on Databricks, integrating LLMs, vector search, and agentic workflows with Python and Azure.
Machine Learning Engineer (Computer Vision & Azure) | Hybrid Setup
Build and deploy computer-vision and multimodal AI models on Azure to improve retail insights and consumer engagement using Python, PyTorch, and ML pipelines.
AI/ML Engineer - Computer Vision & Production Pipelines
Designs and deploys scalable ML workflows for computer vision, validates training data, and automates production pipelines using Azure ML, PyTorch, and MLflow.
Back-End Developer with AI Experience
Build and maintain scalable back-end systems and APIs, integrating AI/ML models into production applications for a remote-first startup.
Enterprise Data Scientist: AI, Cloud & Impact
Build and deploy large-scale AI solutions for enterprise customers, using Python/C++ and cloud platforms, while collaborating with cross-functional teams to solve complex business problems.
Big Data Engineer
Design and build end-to-end big-data pipelines using Spark, Python/Scala, Airflow, and cloud platforms (AWS/Azure/GCP) to process and store data at scale.
Machine Learning Engineer, Computer Vision – Azure
Build and maintain ML pipelines, train computer-vision models, and deploy them on Azure to solve business problems using Python, PyTorch, and SQL.
AI & Machine Learning Engineer II - Mexico
Build and deploy AI/ML models and data pipelines to power logistics solutions, working with Python, cloud platforms, and MLOps tools.
AI Machine Learning Engineer
Designs and deploys ML models for localization workflows using Python, TensorFlow, and AWS services; owns projects from conception to production.
Data Engineer - Databricks
Build and migrate ETL/ELT pipelines on Databricks and AWS for a global fund-services provider, using Delta Lake, Spark, and AWS Glue.
Streaming Data Engineer
Build end-to-end streaming data pipelines using Kafka, Flink, Spark Streaming and cloud services to process real-time data and deliver low-latency insights for enterprise clients.
Senior Data Engineer (MOSAIC AI)
Build and deploy AI agents using Databricks Mosaic AI, LangChain/LangGraph, and RAG pipelines; integrate base models and implement MLOps best practices.
Data Engineer (AI Experienced)
Build and deploy AI systems for cost estimation and optimization, including LLM-powered applications and MLOps pipelines integrated with enterprise platforms.
Data Engineer - Databricks
Build and migrate ETL/ELT pipelines to Databricks on AWS, using Spark, Delta Lake, and AWS Glue to process batch and streaming data for a global fund-services provider.
Databricks Data Engineer
Build and maintain scalable ETL/ELT pipelines on Databricks using PySpark, Delta Lake, and Unity Catalog, then surface insights via BI tools and GenAI-ready datasets.
DevOps Engineer
Builds CI/CD pipelines and LLMOps tooling to deploy and monitor AI-powered apps on Azure, including prompt versioning and model endpoint management.
DevOps Engineer
Build and maintain CI/CD pipelines and LLMOps tooling for deploying, monitoring, and managing LLM-based applications on Azure using Docker, Kubernetes, and Azure DevOps.