Benefits:

• Equity

• Bonus

Education Requirements:

• Bachelor's degree or above in Computer Science or related fields

Experience Requirements:

• 3+ years of work experience in a Machine Learning Engineer or AI Engineer role

• Experience with Video Understanding / Computer Vision

• Experience with LLM Fine-tuning / RAG Systems

• Experience with Backend Systems for AI

Other Requirements:

• Fluent in Python

• Strong System Design Sense

• Solid Engineering Fundamentals

• AI/ML Proficiency

Responsibilities:

• Design and build scalable, low-latency AI inference microservices

• Collaborate to build production pipelines for Video Understanding and LLMs

• Ensure all code is modular, type-safe, and maintainable

• Profile and optimize Python/C++ code and model inference layers

• Conduct research on cutting-edge LLMs and refactor experimental code

Benefits:

• Offers Equity

• Bonus

Experience Requirements:

• Expert-level ability to debug Kubernetes internals

• Operate stateful workflow engines (Temporal) at scale

• Proven track record as a primary first responder

• Experience architecting Datadog SLOs

• Strong proficiency in Python or Bash

Other Requirements:

• Experience scaling GPU/video rendering workloads (preferred)

• Experience with Terraform

• Experience with Milvus and Postgres

Responsibilities:

• Architect high-throughput, isolated processing clusters

• Drive general improvements in production Kubernetes environments

• Overhaul Datadog observability suite to reduce Time-to-Detect

• Serve as the first line of defense during outages

• Lead the post-mortem process to determine Root Cause

Benefits:

• Competitive equity (ISOs)

• Performance-based bonus

Experience Requirements:

• 3+ years shipping production-grade software

• Experience with video infrastructure (preferred)

• Experience with vector databases or high-volume data pipelines (preferred)

Other Requirements:

• Technically versatile (React, Node.js, Python)

• AI-Native Mindset

• Knowledge of GCP, Redis, MongoDB

• Comfortable troubleshooting complex network/server issues

Responsibilities:

• Rapidly ship prototypes and production releases of AI curation improvements

• Co-innovate with social media creators to validate product initiatives

• Transform research artifacts into scalable services

• Design and ship the dashboard connecting video content to ROI

• Implement semantic search using high-dimensional vector databases

Benefits:

• Competitive equity packages (ISOs)

• Comprehensive medical, vision, and dental coverage

• Flexible paid time off

• Equipment, software, and office furniture budget

• Free lunch and dinner

Experience Requirements:

• Expert-level ability to debug Kubernetes internals

• Operate stateful workflow engines (Temporal) at scale

• Proven track record as a primary first responder

• Experience architecting Datadog SLOs

• Strong proficiency in Python or Bash

Other Requirements:

• Experience scaling GPU/video rendering workloads (preferred)

• Knowledge of Terraform

• Familiarity with Milvus and Postgres

Responsibilities:

• Architect high-throughput, isolated processing clusters

• Operationalize scaling strategies for Temporal and Kubernetes

• Overhaul Datadog observability suite to reduce TTD

• Serve as the first line of defense during outages

• Lead the post-mortem process to determine Root Cause