Point your AI agent at freehire and let it find you a job. A CLI and an MCP server over the whole job API — no browser.
Lead the design and deployment of advanced AI models, including LLMs and multimodal systems, using deep learning and statistical methods to solve complex business and research challenges.
Build and operate sovereign AI infrastructure for government clients, deploying GPU clusters in air-gapped data centers and cloud (Azure/GCP) using Kubernetes, GitOps, and offline artifact pipelines.
Build and scale AI agents and ML pipelines using Python, PyTorch/TensorFlow, and frameworks like LangChain; integrate LLMs, vector DBs, and cloud-native systems.
Build and maintain AI-powered data pipelines and infrastructure for document automation, deploying LLM agents and ensuring scalable, reliable AI systems in production.
Build and maintain a self-serve data platform for a large classifieds marketplace, owning batch and streaming pipelines, lake management, and APIs that power analytics and ML workloads using Databricks, AWS, Spark, Python, Kafka, and Airflow.
Build and maintain scalable data pipelines on Google Cloud using BigQuery, Cloud Storage, and Kubeflow, while automating infrastructure with Terraform, Kubernetes, and CI/CD tools.
Lead a team building AI-powered data and ML systems for eBay sellers, including pricing intelligence, demand recommendations, and seller analytics using Java/Kotlin, Python, Spark/Scala, and LLMs.
Lead AI strategy and build large language models for a healthcare platform, collaborating with regional teams to deploy and scale ML systems end-to-end.
Build, optimize, and integrate AI models (CV/NLP) into banking systems using Python, TensorFlow/PyTorch, and MLOps pipelines.
Build and maintain sovereign, self-hosted AI infrastructure on Italian national clouds, deploying Kubernetes clusters and MLOps toolchains while ensuring GDPR/AGID compliance.
Builds and deploys open-source data and AI platforms using Python, Kubernetes, Kubeflow, and MLFlow for cloud and on-prem environments.
Builds and maintains open-source data platforms using Python and Kubernetes, focusing on analytics tools like Kubeflow and MLFlow for cloud and on-prem deployments.
Build and run the AIOps platform that keeps AI models, LLM pipelines, and agents reliable, scalable, and cost-efficient in AWS/Azure.
Contract DevOps Engineer builds and maintains AWS-based CI/CD pipelines, Kubernetes clusters, and observability for a global SaaS platform using ArgoCD, GitHub Actions, and Splunk.
Build and run the cloud platform that powers the company’s AI services on AWS and Kubernetes, automating deployments with Terraform and CI/CD while supporting MLOps workflows like SageMaker, MLflow, Airflow and Kubeflow.
Build and maintain AI/ML infrastructure for a mobile-gaming company, deploying models that power real-time player experiences and internal tools using Kubernetes, Terraform, and cloud platforms.
Build and maintain high-scale back-end systems for a global travel booking platform using Scala/Kotlin, Kafka, Spark, and modern CI/CD pipelines.
Build and deploy ML models and MLOps pipelines using Python, TensorFlow/PyTorch, and cloud platforms like Azure Databricks for real-time, event-driven data solutions across industries.
Build and maintain ML models for an energy-data platform that collects sensor and consumption data from buildings to help owners cut costs and emissions.
Build open-source AI/ML and data analytics platforms using Python and Kubernetes, leveraging tools like Kubeflow and MLFlow for public cloud and private infrastructure.
We couldn't check your fit for this role — add a CV to your profile to see it next time.