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.
Build and scale ML systems for identity resolution, audience intelligence, and personalization across WBD’s streaming brands using Databricks, Snowflake, and AWS.
Build and deploy ML systems for identity resolution, audience modeling, and personalization on AWS/Databricks, using PyTorch, Spark, and agentic AI workflows to power WBD’s streaming and ad platforms.
Lead the machine-learning systems that rank, recommend, and retrieve restaurants and menu items for millions of diners, using deep learning, embeddings, and LLMs to optimize conversion and long-term value.
Leads AI/ML and generative AI projects, designing RAG pipelines, LLM-based systems, and production-ready models while owning end-to-end delivery, strategy, and cross-functional team leadership.
Design and maintain AWS cloud infrastructure for AI/ML systems, including GPU clusters, CI/CD pipelines, and observability, while collaborating with AI engineers and data scientists.
Build and fine-tune AI models for security alert triage and risk scoring using enterprise telemetry, then deploy a multi-model routing layer that keeps costs predictable while improving accuracy over time.
Senior Machine Learning Engineer, Recommendation and Personalization Location: Los Angeles, California, United States; San Francisco, CA, United States Department: Center for Data & Insights (CDI) About Crunchyroll…
Build and deploy agentic AI systems on AWS that automate tax and compliance workflows for fintech and enterprise customers using Strands Agents, Bedrock, and Lambda.
Lead the design, training, and deployment of production-grade ML models in Python for high-growth clients, using cloud infrastructure and MLOps tooling to drive business decisions.
Build and deploy ML models and MLOps pipelines using Python, TensorFlow/PyTorch, and cloud platforms like Azure Databricks for real-time data-driven solutions.
Builds and deploys ML models (deep learning, MLOps) for clients across industries, using Python/TensorFlow/PyTorch, Kafka, and cloud platforms like Databricks/Fabric, while collaborating with cross-functional teams to deliver scalable, real-time data-driven solutions.
Analyze payment fraud patterns, design rules to block fraud while keeping approvals high, and automate reviews using data and AI/ML models.
Build and deploy AI/ML models (LLMs, NLP, deep learning) for client projects, from requirements to production, using Python, SQL, and cloud tools (AWS/GCP/Azure).
Who We Are? Right now, someone in your company is pasting something they shouldn't into an AI tool. A contract into a chatbot. A customer list into an assistant that got installed last week. Source code into a…
Build and maintain AWS-based MLOps platforms for GenAI models, automating pipelines with SageMaker, MLflow, and CI/CD while ensuring secure, scalable deployments.
Leads machine learning initiatives for an online gaming platform, designing and deploying scalable models to enhance security, user experience, and data-driven decisions for hundreds of thousands of users.
Design and advise on scalable GenAI/ML and Agentic architectures on AWS, helping customers implement LLMs, RAG, vector DBs, and MLOps while optimizing for security, cost, and performance.
Lead AI/ML strategy and teams at early-stage startups, defining product roadmaps and deploying generative AI systems using Python, PyTorch, and cloud MLOps stacks.
Principal AI/ML Engineer to architect and deploy cutting-edge models (LLMs, transformers) and lead AI strategy at high-growth startups in SignalFire’s portfolio.
Build and deploy AI models from scratch for early-stage startups, leading RAG pipelines, agent architectures, and LLM-powered systems in Python with PyTorch/TensorFlow.
We couldn't check your fit for this role — add a CV to your profile to see it next time.
){kind=logo}