turbalance

Role Description Turbalance AI is looking for a Forward Deployed Engineer to join our growing team! In this role, you'll be a key technical partner for our customers across the entire customer lifecycle—from pre-sales technical support through onboarding, implementation, and ongoing enablement. - Customer Engagement & Enablement: - Guide customers through onboarding, ensuring they are fully prepared and proficient in using our solutions. - Conduct training sessions and develop enablement materials tailored to customer needs. - Proactively identify opportunities for customers to maximize platform value. - Act as a trusted technical advisor, offering best practices and solutions to common challenges. - Technical Implementation & Support: - Provide hands-on support for solution setup and configuration within customer environments. - Support API and system integrations with existing customer infrastructure. - Diagnose and resolve technical issues, collaborating with engineering teams on complex problems. - Troubleshoot connectivity, performance, and deployment challenges. - Pre-Sales Technical Support: - Support the sales team with domain expertise and technical credibility. - Demonstrate technical capabilities and solution fit during the sales process. - Design integration approaches and implementation plans for prospective customers. - Cross-Functional Collaboration: - Gather customer feedback and relay insights to product and engineering teams. - Reduce workload on core engineering teams by handling customer-facing technical work. - Provide responsive, dedicated customer engagement to build long-term relationships. Qualifications - Strong background working with diverse technology stacks, with ability to quickly learn and adapt to new technologies. - Solid coding foundation with C++ and Python as must-haves; demonstrable understanding of robust software development principles. - Understanding of the interplay between software and hardware behavior and performance (GPUs, CPUs, networking). - Proficiency with Kubernetes for deploying, scaling, and managing containerized applications. - Genuine desire to help customers achieve their goals, with excellent communication and interpersonal skills; prior experience in deep, durable customer-facing technical roles. - Ability to thrive in a fast-paced, multidisciplinary, dynamic environment while managing multiple priorities. Requirements - Experience with additional programming languages (PyTorch, Rust, Go). - Familiarity with cloud platforms (AWS, Azure, GCP). - Experience with OpenStack and/or Slurm. - Knowledge of network operating systems and hardware (Arista, Cisco, Mellanox) and network engineering (especially switching). - Familiarity with AI/HPC networking protocols (RoCE and/or InfiniBand). - Demonstrable experience with performance characterization and profiling, especially for processors, memory systems, and networks. - Experience with kernel debugging. - Experience with LLM deployments, even at small scale. - Background in infrastructure design, SLAs, system design, and incident response. - Field Applications Engineering or similar hardware-focused customer engineering experience. Benefits - Competitive pay & perks – because great work deserves great rewards. - Work on your terms – flexible hours and remote-friendly culture. - Fast lanes, no red tape – flat hierarchies and rapid decision-making. - Make it happen - your ideas aren’t just heard – they become reality. - Right place, right time – be part of our growth story and build a career-defining legacy. - Globality design – work with a diverse, international team across Germany and the US. - Work with the best – work alongside exceptional engineers and raise the bar together.

• Design and implement a trace collection system for distributed LLM workloads • Validate that collected traces accurately reflect real workload behavior • Integrate with and instrument major LLM frameworks to extract meaningful execution data • Use collected traces as input to discrete event simulations • Analyze trace data to surface bottlenecks and inefficiencies