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At Zimmer Biomet, we believe in pushing the boundaries of innovation and driving our mission forward. As a global medical technology leader for nearly 100 years, a patient’s mobility is enhanced by a Zimmer Biomet…
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products. The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is…
Forward Deployed Engineer embedding with client teams to deploy, integrate, and scale enterprise Generative AI solutions on Google Cloud Platform, working with LLMs, vector databases, RAG pipelines, and GKE infrastructure.
hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role. JOB DESCRIPTION Join a high performing team of applied AI experts to drive innovation and new capabilities in the…
About Tapestry Tapestry is a group within Google working to build the AI-powered electric grid. We are tackling one of the world’s most important infrastructure challenges: helping the energy system become more…
MLOps Engineer builds and scales automated pipelines for machine learning models in a large e-commerce trust-and-safety team, using Kubernetes, Docker, ClearML, and Nvidia Triton.
Join the leader in entertainment innovation and help us design the future. At Dolby, science meets art, and high tech means more than computer code. As a member of the Dolby team, you’ll see and hear the results of…
Cloud Infrastructure/DevSecOps Engineer deploying and managing AWS EKS clusters, Terraform infrastructure, GitLab CI/CD pipelines, and observability tooling (Grafana/Loki/Prometheus) for defense mission systems.
We’re looking for a tech leader ready to take their career to new heights. Join the ranks of top talent at one of the world’s most influential companies. As a Senior Principal Software Engineer at JPMorganChase within…
Job Title: DevOps Engineer – AI/ML Platform Experience: 8–12+ years About the Role We are seeking a skilled DevOps Engineer with experience in AI/ML infrastructure to design, build, and maintain scalable, secure, and…
The MLOps Engineer will design and implement automated pipelines for model deployment, monitoring, and retraining within Data Science projects. The role requires expertise in cloud-based ML platforms, CI/CD/CT practices, and container orchestration using tools like Kubernetes, AWS SageMaker, and Kubeflow.
The AI Engineer will build and scale the infrastructure and operations platform for AI products, focusing on MLOps, automation, and observability. The role involves managing ML and LLM pipelines in AWS and Azure environments while collaborating with cross-functional data teams.
The DevOps engineer will manage the full lifecycle of microservice-based products, focusing on CI/CD, infrastructure automation, and Linux environment optimization. Key technologies include Docker, GitLab CI, Ansible, Terraform, and Python.
This Senior Machine Learning Engineer role in the Healthcare & Life Sciences unit involves leading end-to-end AI/ML project delivery, including hands-on development of RAG pipelines, agentic workflows, and MLOps systems. The position requires deep expertise in Python, PyTorch/TensorFlow, and modern AI frameworks to build scalable, production-grade solutions.
Designs, builds, and deploys AI/ML systems on Google Cloud to solve business problems, focusing on model optimization, MLOps pipelines, and agentic AI workflows for Crate & Barrel’s core products.
Build and deploy AI models and systems for Amgen’s AI Studio, turning business challenges into scalable AI products using Python, SQL, GenAI, RAG, and cloud-native tools.
Designs and evaluates scalable machine learning architectures for a large U.S. bank, guiding adoption of cloud-based ML platforms and MLOps practices to enable predictive modeling and AI-driven financial solutions.
Senior ML Engineer designing, implementing, and supporting AI/ML solutions and scalable ML infrastructure on GCP, using Python with frameworks like TensorFlow/PyTorch/LangChain, Docker, Terraform, and ML orchestration tools.
Lead the design, development, and deployment of AI and ML models and systems, focusing on scalability, reliability, and performance. Collaborate with cross‑functional teams, including data scientists, software…
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