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.
Data Engineer responsible for designing, developing, and maintaining scalable data pipelines on Databricks and Azure, supporting analytics and ML workloads with ETL, streaming, and batch processing.
Location: San Francisco, California or Seattle, Washington Employment Type: Full time, Hybrid About the Team The Machine Learning team — internally known as "Potato Radius" — builds the training pipelines,…
Designs and optimizes scalable, secure data platforms for clinical research analytics, AI/ML, and regulatory compliance using cloud-native tools and distributed systems.
Staff Data/Platform Engineer designing and scaling distributed data systems (Kafka, Flink, Spark, Delta Lake) for real-time streaming pipelines, analytics, and AI infrastructure at a conversational AI company. Remote in Brazil.
Build and maintain the data infrastructure platform at a fintech company, deploying tools like Airflow and Flink and managing AWS storage services such as DynamoDB and RDS.
Senior Backend SDE owning microservices and data pipelines handling 200K+ QPS and petabyte-scale data at an AI-powered e-commerce discovery platform, using Go/Python/Java, SQL/NoSQL databases, and cloud infrastructure.
Build and scale large-scale data pipelines and platforms for an AI-powered e-commerce discovery engine, using Spark, Kafka, Flink, and GCP to power personalization, recommendations, and ML systems.
InMobi Advertising is a global technology leader helping marketers win the moments that matter. Our advertising platform reaches over 2 billion people across 150+ countries and turns real-time context into business…
Lead the design and delivery of real-time data pipelines and backend microservices for InMobi’s DSP, processing billions of bid-stream events daily to power bidding intelligence, audience targeting, and campaign analytics using Python/Java/Scala, Kafka/Flink, StarRocks, and Kubernetes.
Builds and maintains Apple’s AI & Data Platforms, optimizing big data infrastructure for analytics, AI/ML apps, and reporting via distributed systems and cloud platforms.
The Senior Backend Software Engineer will design and maintain Java-based backend services for restaurant POS systems, focusing on order lifecycles, payments, and device synchronization. The role involves optimizing event-driven systems and APIs to ensure low latency and consistency across cloud and physical infrastructure.
Designs, operates, and optimizes Medallia’s distributed platform infrastructure (Kafka, Elasticsearch, Spark, etc.) to ensure reliability, scalability, and performance for its Experience Cloud SaaS.
Designs, operates, and optimizes Medallia’s distributed platform infrastructure (Kafka, Elasticsearch, Spark, etc.) to ensure reliability, scalability, and performance for global SaaS services.
Builds and operates a real-time, event-driven microservices platform for processing pentest data at scale, transforming batch-era logic into streaming-friendly designs for cybersecurity insights.
Urbiotica is seeking a mid-level software engineer to design and maintain real-time data streaming pipelines for their IoT sensor network. The role focuses on processing large-scale data using technologies like Apache Flink, Python, and Apache Iceberg to support smart city solutions.
This role involves building a global Data Mesh platform using a Lakehouse architecture, focusing on batch and streaming data pipelines. You will work with technologies like Apache Spark, Databricks, Kafka, and cloud storage to enable secure data sharing and governance.
Staff ML Engineer building and owning end-to-end production ML systems for revenue management and pricing optimization in a hospitality SaaS platform, using Python, AWS SageMaker, Airflow, and MLOps tooling.
At Moss, we give finance professionals the power to automate their day-to-day and make forward-thinking decisions. Our team and culture make us unique — we’re driven by impact and growth, where every one of us strives…
Senior Software Engineer on Google Cloud Dataproc, enhancing Apache Spark and Lake House technologies (Iceberg, Hudi, Delta Lake) for performance, reliability, and security on large-scale distributed systems.
We couldn't check your fit for this role — add a CV to your profile to see it next time.
