Senior Machine Learning Engineer, ML Infrastructure – Online

Job not on LinkedIn

🔥 1 hour ago

☕ Washington – Remote

☕ Washington – Remote

💵 $187.2k - $243.3k / year

⏰ Full Time

🟠 Senior

👷 Infrastructure Engineer

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UNITYTECH CONSULTING

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

💼 Consulting

Consulting

UNITYTECH CONSULTING is a technology-focused consulting firm (inferred from the name) that appears to provide professional consulting services. There is no company-specific information in the supplied data (the provided text contains unrelated website demo entries for "Outdoor Adventure" themes), so this description is conservative and based primarily on the company name. No details about offerings, customers, or size were provided.

📋 Description

• Design and operate large-scale online inference infrastructure serving production ML models with low latency and high reliability • Develop infrastructure supporting distributed training workflows • Integrate ML pipelines with workflow orchestration systems for reliable multi-stage training workflows • Optimize model performance through compilation, GPU/CPU utilization improvements, request scheduling, kernel fusion, and runtime tuning • Improve observability through latency, throughput, error-rate, cost, saturation, and model-health monitoring • Partner with ML engineers to accelerate model iteration while maintaining production safety, scalability, and cost efficiency • Improve reliability and reproducibility of model serving workflows, including packaging, artifact validation, compatibility testing, and deployment automation • Lead architectural improvements to make the online ML platform more robust, user-friendly, scalable, and cost-efficient

🎯 Requirements

• Experience building and operating production-grade online ML inference systems • Experience with model serving frameworks such as NVIDIA Triton Inference Server, TorchServe, Ray Serve, TensorFlow Serving, or similar systems • Experience optimizing inference workloads using dynamic batching, model compilation, quantization, GPU acceleration, GPU kernel optimization, caching, or runtime tuning • Strong experience with distributed systems, Kubernetes, autoscaling, service reliability, and production observability • Strong programming skills in Python, with practical experience working on production ML systems and high-scale services • Experience with PyTorch and modern model deployment workflows, including model packaging, validation, and serving lifecycle management • Experience designing infrastructure for safe model rollout, canary testing, A/B experimentation, and automated rollback • Strong systems thinking and ability to reason about latency, throughput, reliability, scalability, and cost tradeoffs • Proven ability to lead technical direction and influence architectural decisions across teams without formal authority • Sufficient knowledge of English for professional verbal and written exchanges • Work visa/immigration sponsorship is not available for this position • Relocation support is not available for this position

🏖️ Benefits

• Comprehensive health, life, and disability insurance • Commute subsidy • Employee stock ownership • Competitive retirement/pension plans • Generous vacation and personal days • Support for new parents through leave and family-care programs • Office food snacks • Mental Health and Wellbeing programs and support • Employee Resource Groups • Global Employee Assistance Program • Training and development programs • Volunteering and donation matching program • Equity awards • Participation in company incentive plans, such as annual discretionary bonuses or sales commissions