
1 - 10 employees
🛍️ eCommerce
🎮 Gaming
📱 Media
eCommerce • Gaming • Media
Strimi is a social live streaming platform geared towards Gen-Z users, emphasizing engagement and interaction. The company promotes itself with the tagline 'The Best Time to be Live,' indicating a focus on real-time content and community-building through live streaming features.
🔥 30 minutes ago
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1 - 10 employees
🛍️ eCommerce
🎮 Gaming
📱 Media
eCommerce • Gaming • Media
Strimi is a social live streaming platform geared towards Gen-Z users, emphasizing engagement and interaction. The company promotes itself with the tagline 'The Best Time to be Live,' indicating a focus on real-time content and community-building through live streaming features.
• Design and implement scalable real-time data integration and Change Data Capture (CDC) solutions using the Striim platform. • Design streaming data architectures connecting enterprise databases, cloud data platforms, messaging systems, and AI/ML environments. • Develop data pipelines that support machine learning workflows, feature engineering, model inference, and real-time AI applications. • Build proof-of-concepts, reference architectures, and deployment patterns for enterprise implementations. • Configure, optimize, and troubleshoot data pipelines across cloud and hybrid environments. • Collaborate with Engineering, Product, and GTM Engineering teams to validate architectural designs, resolve complex technical challenges, and improve platform capabilities. • Participate in architecture reviews, implementation planning, and production readiness activities. • Create technical documentation, architecture diagrams, and implementation best practices. • Evaluate emerging technologies across AI, MLOps, cloud computing, and real-time data streaming.
• 1–3 years of professional experience or equivalent graduate research, internships, or project experience in data science, machine learning, data engineering, cloud engineering, or solution architecture. • Strong foundation in data science, including machine learning algorithms, model selection, feature engineering, and the machine learning lifecycle. • Understanding of modern MLOps practices, including model deployment, inference, monitoring, versioning, and CI/CD for machine learning applications. • Experience or academic exposure to machine learning frameworks and platforms such as MLflow, Kubeflow, Vertex AI, SageMaker, or Azure Machine Learning. • Familiarity with modern data integration concepts, including Change Data Capture (CDC), event-driven architectures, and real-time streaming data pipelines. • Working knowledge of relational and NoSQL databases, including SQL proficiency and database administration fundamentals. • Experience with cloud platforms and modern cloud data ecosystems, including AWS, Azure, GCP, Databricks, Snowflake, BigQuery, Amazon Redshift, or Azure Synapse. • Experience programming in Python or Java and working with REST APIs and JSON. • Understanding of Docker containers and modern DevOps concepts; familiarity with Kubernetes, Git, and CI/CD pipelines. • Strong analytical, troubleshooting, written, and verbal communication skills. • Demonstrated curiosity, adaptability, and a passion for learning emerging technologies in AI, cloud computing, and real-time data streaming. • Bachelor's or Master's degree in Computer Science, Data Science, Software Engineering, Information Systems, or a related technical discipline.
• Competitive salary and pre-IPO stock options • Comprehensive health care plans (medical, dental and vision), including medical and dependent FSA • Paid Time Off (Vacation, Sick & Public Holidays) • The chance to contribute to and shape an upbeat, fully engaged culture
Apply Now🔥 1 hour ago
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