Staff/Lead Software Engineer, AI Infrastructure

PIKA, LLC
United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Microsoft Azure C++ (Programming Language) Software as a Service Code Review Distributed Systems Python (Programming Language) Machine Learning Tensorflow Azure Machine Learning
+9 more
AI Infrastructure Cloud Platform System Large Language Models Generative AI Backend Kubernetes Low Latency Hardware Infrastructure Multiaccess Edge Computing

Job description

We are looking for a Staff/Lead Software Engineer, AI Infrastructure, to play a critical role in building and scaling the core infrastructure that powers Pika’s AI capabilities. In this position, you will lead the design and implementation of GPU infrastructure, AI model serving APIs, and general AI infrastructure execution-enabling cutting-edge machine learning features that drive our products.

You will be responsible for architecting robust, distributed systems optimized for high-performance AI workloads, large-scale GPU orchestration, and low-latency, reliable API serving. Your work will directly impact the way users experience and interact with generative AI at scale. As a senior technical leader, you’ll also mentor engineers, drive best practices, and set the technical vision for AI infrastructure at Pika.

What You’ll Do

  • Design, develop, and maintain scalable GPU infrastructure for training and serving state-of-the-art AI models
  • Architect and optimize high-throughput, low-latency APIs for AI model serving and inference
  • Lead the orchestration, scheduling, and efficient utilization of heterogeneous GPU resources across clusters
  • Build and support robust systems for model deployment, monitoring, scaling, and reliability in production environments
  • Collaborate with ML, backend, and platform engineering teams to deliver seamless AI-powered product features
  • Drive technical direction, code reviews, and mentorship across the AI Infrastructure team

Requirements

  • Strong experience (5+ years) as a software engineer working on systems infrastructure, including hands-on work with ML serving and GPU orchestration
  • Deep knowledge of distributed systems, Kubernetes (or similar orchestration frameworks), and cloud-native infrastructure (AWS/GCP/Azure)
  • Proven expertise in building and optimizing APIs for large-scale AI model serving (TensorFlow Serving, Triton, TorchServe, or similar)
  • Familiarity with the challenges of high-throughput, scalable GPU fleet management, scheduling, and efficient model execution
  • Proficiency in backend languages such as Python, Go, or C++, and experience optimizing for performance and reliability
  • Ownership mentality and the drive to solve complex problems independently in ambiguous, high-growth environments
  • Excellent communication, collaborative, and mentorship skills

Nice to Have

  • Experience with multi-modal AI model infrastructure (LLMs, generative models, video/image/speech models)
  • Background in building infra for multi-tenant SaaS, enterprise AI/ML platforms, or operational automation at scale
  • Previous startup experience or experience leading high-impact projects through ambiguity and rapid iteration
  • Experience with competitive coding or large-scale distributed computing environments

Benefits & conditions

  • Competitive salary in the AI industry
  • Equity in a rapidly growing team shaping the future of AI
  • Comprehensive health benefits, monthly stipends, and company retreats
  • A supportive and collaborative office culture-everyone builds, ships, and learns together

About Pika

At Pika, we’re building the infrastructure that empowers everyone to create videos and express ideas through advanced AI. Our team is passionate about removing technical barriers to creativity, and we thrive on working together to solve hard problems. We’re based in Palo Alto, CA, with a collaborative team working in-office 3-5 days a week. FULL_TIME Organization

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