Architect and build production data pipelines and multi-model data stores to serve AI workflows and client-facing applications. Lead the technical direction for data services, ensuring scalability, reliability, and observability under live traffic.
Satalia
12 Remote Job Openings at Satalia
Lead the development of high-performance distributed data processing services using Rust. Design and implement robust code and optimization algorithms to solve complex business problems within an AI-centric product environment.
Design and maintain large-scale data pipelines and polyglot data infrastructure to support AI and BI systems. Build and operate services, APIs, and dbt models to turn multimodal datasets into reliable production products.
Lead the development of an enterprise-quality optimization and ML-based platform for field operations providers. You will be responsible for technology selection, API design, and collaborating with data science teams to deliver performant cloud solutions.
Lead the development of an enterprise-quality optimization and ML-based platform for field operations providers. Responsible for technology selection, API design, and collaborating with data science teams to deliver performant cloud solutions.
Lead the development of an enterprise-quality optimization and ML-based platform for field operations providers. You will be responsible for technology selection, API design, and collaborating with data science teams to deliver performant cloud solutions.
You will explore and prepare datasets while training and evaluating machine learning models under the guidance of senior scientists. Additionally, you will write and maintain production-ready Python code and contribute to the development of LLM-powered systems.
You will build, iterate, and deploy machine learning models while maintaining production pipelines and contributing to LLM-powered systems. Additionally, you will analyze large multimodal datasets to extract insights and write clean, production-quality Python code.
You will build, iterate, and deploy machine learning models while maintaining production pipelines and contributing to LLM-powered systems. You will also analyze large multimodal datasets to extract insights and write clean, production-quality Python code.
You will lead the technical direction for AI projects, including scoping problems, choosing modeling approaches, and building training infrastructure. You are responsible for shipping production-ready AI systems, including agentic pipelines and inference services, while mentoring junior scientists.
You will lead the technical direction for AI projects, including scoping problems, building training infrastructure, and shipping production-grade models. You are responsible for the end-to-end lifecycle of AI systems, from data curation and model selection to monitoring and debugging in production.
Design and deliver production-grade multi-agent systems and AI services for enterprise-scale clients. Implement robust RAG pipelines, agent memory management, and AgenticOps practices to ensure reliable and ethical AI operations.
