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GCP Data & MLOps Engineer — Pipelines & AI
Designs and builds scalable GCP-based data pipelines, MLOps workflows, and cloud-native apps using Dataflow, Kubeflow, BigQuery, Python, and Django.
Senior Machine Learning Engineer - Production AI Leader
Lead end-to-end ML projects: design, build, deploy, monitor, and optimize AI models for production while mentoring peers and setting modelling standards.
GCP Data Engineer
Build and maintain GCP data pipelines and MLOps frameworks using Dataflow, Apache Beam, BigQuery, Kubeflow, and Python for enterprise clients.
Senior Applied AI Engineer
Build and scale an agentic AI platform (Floyd) that turns investment research into structured insights using LLM APIs, vector DBs, and Databricks pipelines, while collaborating with investment teams.
Databricks MLOps Engineer
Build and maintain cloud-native AI infrastructure on Databricks and AWS, deploying ML models and LLMs at scale with MLOps pipelines and observability.
Data Scientist - Consumer Technology Platform
Build ML models for retention, recommendations and customer growth on a 4M+ member platform using Python, SQL and Databricks.
Site Reliability Engineer Dynatrace
Build and maintain cloud-scale observability and security platforms using Dynatrace, AWS, and Azure to detect runtime vulnerabilities and protect workloads before incidents occur.
Onsite Auckland ML & Computer Vision Intern (Data Science)
Build and deploy ML models for computer vision systems in an R&D team, improving data pipelines and MLOps workflows.
Staff Backend Engineer - Node/Typescript
Build and own the backend platform for a real-time 3D commerce environment using Node.js/TypeScript, PostgreSQL, AWS, and CI/CD pipelines in a fast-paced startup.
AI/ML Architect / MLOps Architect
Designs and deploys scalable AI/ML systems, covering data pipelines, model training, deployment, monitoring, and Agentic AI integration.
Machine Learning Engineer Fraud Detection
Build and maintain production-grade fraud detection models using Python, ML, and graph databases, serving low-latency inferences via REST APIs on GCP and Databricks.
AI/ML Engineer - Hartford, CT, Princeton, NJ, Newark, NJ, New York City, NY, Boston, MA.
Build and maintain enterprise-scale ML platforms for model development, deployment, monitoring, and governance using MLOps, LLMOps, and cloud-native AI tools.
Staff Platform Architect, Data & AI (Remote)
Designs and evolves enterprise-scale data and AI platforms, including MLOps, semantic layers, and governed access APIs, to enable advanced analytics and intelligent systems across the organization.
Machine Learning Engineer, MLOps
Senior ML Engineer builds and maintains MLOps infrastructure to deploy AI/ML and generative AI systems into production, including APIs, vector databases, and RAG pipelines.
Site Reliability Engineer (Remote)
Senior SRE role building resilient, scalable infrastructure for a globally scaled AI-native platform on AWS and Kubernetes, focusing on event-driven systems, observability, and chaos engineering.
Site Reliability Engineer
Senior SRE role building resilient, scalable infrastructure for a globally scaled AI-native platform, focusing on AWS, Kubernetes, event-driven systems, and observability.
Senior Data Scientist, Generative AI
Build and deploy production-grade LLM applications and agentic workflows that turn unstructured text into business insights, using RAG, prompt engineering, and modern cloud data platforms.
Senior Software Engineer - (Backend,AI)
Build and lead backend systems integrating GenAI/LLMs, designing scalable AI pipelines and agentic workflows in Python/Java/Spring Boot on AWS.
MLOps Platform Developer / Full-Stack AI Engineer
Build and own a full-stack MLOps platform: React/TypeScript frontend, Postgres backend, data pipelines, deployments, and LLM serving stack.