Server-Side / MLOps Engineer at Symbolic Mind We’re seeking an engineer to help scale our server-side systems and MLOps foundation. Responsibilities include expanding infrastructure, developing data and training pipelines, designing benchmarking workflows, and creating fast, reproducible Docker environments for model development. You'll work closely with our research team and play a significant role in how we run, test, and deploy models. Experience with Julia is a plus, but not required. What You’ll Do Run and evolve our Linux-based cloud stack for model training and experimentation. Build and maintain training, evaluation, deployment pipelines. Develop tools for experiment tracking, dataset handling, and reproducible runs. Create and optimize Docker environments for CPU-heavy workloads. Build data ingestion and preprocessing workflows. Design benchmarking tools to measure model performance, speed, and cost. Work side-by-side with researchers to unblock experiments and improve workflows. Analyze the results of experiments and benchmarking. What You Bring Strong experience with Linux systems. Deep comfort with Docker and containerized development. Experience with MLOps workflows: automation, reproducibility, experiment tracking, artifact storage. Ability to build reliable tools for data processing and pipeline automation. Willingness to collaborate tightly with a small, fast-moving team. Nice to Have Julia experience or interest in the language. Background in CPU-optimized ML workflows, HPC, or systems performance. Experience building internal tools or lightweight backend services. Familiarity with LLM experimentation or data-centric ML pipelines. Understanding of performance profiling in CPU-first environments. Who You Are You are a team player who enjoys tackling deep technical problems, simplifying complex workflows, and building reliable systems that enable researchers to move quickly. You like working close to the metal, are comfortable operating without extensive orchestration layers, and value clean, scalable infrastructure. Why Join Us Real ownership and meaningful equity. 401(k) with employer match for added retirement savings. Help build the core of a next-generation AI platform. Flexible remote/hybrid environment. A sharp, collaborative team focused on real engineering, not hype. A diverse, open culture that values curiosity, rigor, and strong ideas.