ML Platform Backend Engineer

We are looking for an exceptional engineering technical leader to join our growing team at Nightfall. As a senior, hands-on, technical engineer in the Engineering organization, you will drive execution, provide solid technical expertise, raise the engineering bar of the team, and contribute towards shaping the long-term architecture of the platform.

This is a hybrid role based out of our San Francisco office. 

Responsibilities

• Drive great execution, work with the team to set clear goals, and deliver against them
• Hands-on, technical design and coding
• Help shape the long-term architecture of the platform keeping scalability and reliability into account
• Help to recruit, inspire a high performing and creative engineering team
• Implement best of practices in a fast-paced engineering environment
• Champion engineering excellence and culture, establish metrics for regular improvement
• Participating in the team's oncall rotation and help drive operational excellence

Requirements

• Minimum 5+ years of hands-on technical development experience
• Minimum 3+ years of experience mentoring and leading engineering teams
• Experience programming in Python, Go, Java, C++ or related language
• Experience designing and building low latency and high throughput systems based on highly scalable microservices-based architectures
• A foundational understanding of multi-threaded programming, concurrency primitives, and data structures using Python, Go or other frameworks
• Expertise in deploying machine models for inferencing in real-time production environments using a variety of Deep Learning frameworks such as PyTorch, TorchScript or Tensorflow, and the ability to solve complex, cross-language, performance and scalability issues associated with them.
• BS/MS in Computer Science or a related technical field
  
  

Bonus Points

• Experience working in high growth venture-backed startups
• Blog, teach, mentor, or help others learn outside of your day to day responsibilities
• Experience training and deploying NLP based machine models or LLMs is a big plus.
• Familiarity with AWS and  managed infrastructure
• Familiarity with Docker, Kubernetes, Kafka, gRPC, Redis, KV-stores