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[Remote] Lead Machine Learning Engineer, Inference & Performance

Egen · Anywhere

Full-timeLeadPythonKubernetes

About the Role

Note: The job is a remote job and is open to candidates in USA. Egen is a fast-growing and entrepreneurial company with a data-first mindset. As a Senior AI Engineer, you will be responsible for the full lifecycle of AI features, focusing on optimizing performance and collaborating with clients to create scalable AI architectures. Responsibilities Optimize Inference: Build and tune production LLM serving with vLLM and SGLang—maximizing throughput and minimizing latency through batching, paged attention, quantization, and KV-cache strategiesProfile & Accelerate Training: Instrument and profile training runs to find bottlenecks, then resolve them with the right attention implementations (e.g. FlashAttention) tuned to the underlying hardware (H200, GB200)Engineer for the Hardware: Apply a working understanding of GPU architecture and attention internals to choose the right approach per accelerator, rather than relying on defaultsServe at Scale: Deploy and operate multiple models within shared GPU clusters on GKE, with autoscaling, efficient bin-packing, and graceful handling of mixed workloadsDrive Efficiency: Own GPU utilization as a first-class metric—measure it, improve throughput-per-dollar, and continuously raise the ceiling on what our fleet can deliverCollaborate & Consult: Work directly with clients to understand performance, latency, and cost requirements, and translate them into pragmatic serving and training architectures Skills Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field5+ years of experience in ML/AI engineering, with a meaningful portion focused on performance, infrastructure, or systemsProven track record of deploying and optimizing models in a production environmentDemonstrated experience profiling and improving GPU utilization for training and/or inferenceMastery of Python and shell scripting; comfort reading and reasoning about lower-level (CUDA-adjacent) performance code is a strong plusHands-on experience with vLLM, SGLash, or comparable high-performance serving stacksSolid grasp of GPU architecture, the fundamentals of LLM inference, and the attention mechanism—including where the bottlenecks live and how FlashAttention and similar techniques address them across hardware generations (H200, GB200)Fluency with profiling tools to diagnose training and inference bottlenecks (compute-bound vs. memory-bound, kernel-level analysis)Strong Kubernetes (GKE) experience—deploying and autoscaling multiple models on shared GPU clusters on Google CloudA strong software engineering foundation—you write clean, maintainable code, measure before optimizing, and understand the full SDLCOwnership: You take pride in your work and see optimizations through from profile to productionCuriosity: Hardware and serving frameworks change fast; you are a lifelong learner who stays ahead of the curveRigor: You measure before you optimize and let data, not intuition, guide where you spend effortConsultative Spirit: You enjoy interacting with clients and can translate technical complexity into business valueEthics: You prioritize responsible AI development and data privacyExperience with Classic Machine Learning (neural nets, training, tuning) is a strong plusKnowledge of Data Engineering and SQL Benefits Comprehensive Health InsurancePaid Leave (Vacation/PTO)Paid HolidaysSick LeaveParental LeaveBereavement Leave401 (k) Employer MatchEmployee Referral Bonuses Company Overview Egen is a technology services company with leading capabilities in cloud, data engineering, analytics, AI, and platform engineering. It was founded in 2000, and is headquartered in Naperville, Illinois, USA, with a workforce of 501-1000 employees. Its website is https://egen.ai. Company H1B Sponsorship Egen has a track record of offering H1B sponsorships, with 7 in 2026, 58 in 2025, 50 in 2024, 60 in 2023, 111 in 2022, 49 in 2021, 79 in 2020. Please note that this does not guarantee sponsorship for this specific role.

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