Junior Solutions Architect – MLOps, Real-Time Data Integration

Stelle nicht auf LinkedIn

🕒 vor 27 Tagen

🇺🇸 Vereinigte Staaten – Remote

💵 $120.000 - $130.000 / Jahr

⏰ Vollzeit

🟢 Junior

💻 Lösungsingenieur

👻 Geisterscore 2%

Was es bedeutet: wie wahrscheinlich diese Stelle offen bleibt, ohne dass aktiv eingestellt wird.So liest du es: 60 % oder höher heißt, wir halten das für einen Geisterjob. Niedrigere Werte sind weniger bedenklich.Wie wir werten: Dauer offen, Neuveröffentlichungen, offene Stellen vs Teamgröße, wie schnell Stellen geschlossen werden, und ob ein Gehalt angegeben ist.Hinweis: eine Schätzung aus öffentlichen Daten, kein Urteil über das Unternehmen. Echte Stellen können hoch punkten, nutze es also als Hinweis, nicht als Fakt.

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Beschreibung

• 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.

🎯 Anforderungen

• 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.

🏖️ Vorteile

• 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