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NOTE: This is a 1-year, Fixed-Term Position. Are you an AI/GenAI engineer who loves shipping real systems? Join Stanford’s Enterprise Technology team to design, implement, and support AI solutions across university use…
Our team members are the key to our company’s success, and their health and well-being, as well as that of their families, is very important to us. We offer a comprehensive benefits package that allows our team members…
Senior Data Engineering Manager leading multiple teams at McKesson, overseeing Azure Data Platform (Data Factory, Synapse, ADLS), Databricks Lakehouse, and distributed data processing with Python, Scala, SQL, and Spark.
Mid-level Data Scientist building machine learning and applied AI solutions for clients using Python, Databricks, and cloud platforms (GCP, Azure) in a remote, Americas-collaborative role.
Hands-on Quantitative Risk Lead building and deploying production-grade Python microservices for VaR engines, derivatives pricing, and CIRO 5000 regulatory margin models, while managing a small quant team at Wealthsimple.
Senior Data Scientist owning the full ML production lifecycle—scaling deep learning models from R&D to reliable production systems, building data/feature pipelines, and establishing MLOps standards. Core stack includes Python/Go/Java, GCP (Vertex AI, BigQuery), Docker, Kubernetes, and MLflow/Kubeflow.
Senior ML Engineer leads end-to-end production ML systems for Amperity’s AI-first customer data platform, focusing on identity resolution, segmentation, and predictive modeling at scale. Owns architecture, deployment pipelines, and MLOps tooling while collaborating with cross-functional teams to deliver measurable business impact.
Singtel is where Technology meets Purpose. We're building an AI-first telco for the future—connecting people, businesses and communities through trusted networks, intelligent digital services and next-generation…
Designs and leads enterprise-scale AI/ML and Generative AI solutions, focusing on LLMs, RAG architectures, and cloud-based deployments while mentoring teams and ensuring governance.
Senior DevOps Engineer responsible for CI/CD, observability, and developer tooling at a global fundraising platform, using Kubernetes, Jenkins, Prometheus, and Grafana.
Design and run tests to ensure AI models are accurate, fair, and secure, using tools like PyTest and TensorFlow Model Analysis.
Develop, fine-tune, and deploy LLMs and ML systems for a B2B SaaS org-chart platform, building RAG pipelines, MCP servers, and Python microservices integrated into the web and cloud stack.
Automate the deployment of general-purpose robot control stacks using CI/CD pipelines, infrastructure as code, and cloud infrastructure, working across a hybrid environment to support ML model and software delivery.
An AIOps/MLOps Engineer designing and maintaining MLOps pipelines, AI/ML infrastructure on Azure, CI/CD automation, and monitoring/observability solutions while collaborating with data scientists and software engineers.
Senior ML Platform Engineer (contract) building and scaling ML pipelines, MLOps workflows, and Databricks-based platform components for financial services client engagements.
Senior Cloud Engineer designing and administering Azure infrastructure for an enterprise data and AI platform, with daily hands-on work in Terraform, Azure Databricks, ADLS Gen2, Azure Data Factory, and Azure Machine Learning.
Alt is unlocking the value of alternative assets, starting with the $5 B trading-card market. We let collectors buy, sell, vault, and finance their cards in one place and we are backed by leaders at Stripe, Coinbase,…
Principal Cloud Architect designs scalable cloud infrastructure, data platforms, and AI-augmented review workflows, prototypes patterns, and hands them off to engineering teams.
Software engineer on Apple's Platform Reliability Engineering team, designing and operating large-scale distributed systems powering GenAI, ML, and big data platforms using Kubernetes, Spark, and other open-source technologies in hybrid cloud environments.
Platform Architect bridging ML infrastructure and SRE on GCP — you'll design and operate model serving, inference infrastructure, reproducible ML pipelines, and GitOps workflows using Terraform, Kubernetes (GKE), ArgoCD, and BigQuery.
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