Bee Talents

Artificial Intelligence

• Lead full‑cycle recruiting across engineering, product, operations, GTM, and leadership roles
• Own the entire talent function: strategy, systems, execution, outcomes
• Build the hiring plan with founders and translate business priorities into a recruiting roadmap
• Design scalable recruiting infrastructure: scorecards, interview loops, analytics, documentation
• Source and engage passive candidates for senior and hard‑to‑fill roles
• Manage external recruiting partners when needed
• Build AI‑powered hiring systems (intake agents, AI screeners, automated workflows)

Talent & Operations Manager

Backend Engineer

• Design and implement AI inference and model training cloud products optimized for Kubernetes - from autoscaling inference servers to distributed training jobs across GPU fleets
• Write clean, efficient, and maintainable Go code to power Kubernetes controllers, operators, and custom resources supporting AI workloads
• Build APIs, CLIs, and developer tools that simplify the deployment, lifecycle management, and monitoring of AI applications
• Develop features that optimize serverless container workflows for AI, ensuring fast cold starts, resource-efficient scaling, and workload isolation
• Contribute to system performance, reliability, and security, with a focus on AI-specific challenges such as GPU scheduling, job orchestration, and data throughput
• Stay on top of Kubernetes ecosystem advancements (e.g., K8s-native ML tooling, scheduling improvements, SIGs) and influence our product roadmap accordingly

Software Engineer, Golang – Kubernetes

Product Analyst

• - Self-Service Optimization: Deep dive into the registration → activation → payment flow. Identify where users drop off and propose A/B tests to fix it.
• - Product Qualified Leads (PQL): Analyze usage patterns to identify high-potential customers (e.g., "This startup just spun up 50 GPUs") and signal our Sales team to engage them.
• - Event Tracking Design: You are the owner of our tracking plan. You tell developers exactly which events and properties to track. "If we don't track the 'Error 500' on the billing page, we are flying blind."
• - Dashboarding: Create clear, actionable dashboards in Mixpanel for Product Managers and Execs.
• - Hypothesis Testing: Help PMs formulate and measure experiments. Did the new onboarding flow increase activation? You give the final verdict.

Platform Product Analyst – PLG, Mixpanel Expert

• Contribute to the development of the Everywhere Inference platform - a Kubernetes-based solution enabling scalable and portable AI inference across a wide range of environments.
• Design and implement APIs and developer tools to simplify deployment, management, and monitoring of AI applications.
• Focus on packaging and integrating new ML models into the platform, using Python and common ML frameworks.
• Optimize serverless container workflows for AI workloads, ensuring performance, scalability, and seamless autoscaling.
• Collaborate with customers to fine-tune ML model performance and support their unique use cases.
• Work with cross-functional teams to improve the AI applications marketplace and ensure smooth model onboarding and lifecycle management.
• Stay current with trends in Kubernetes, machine learning, and MLOps, and help drive innovation within the platform.

Talent & Operations Manager

Software Engineer, Golang – Kubernetes

Platform Product Analyst – PLG, Mixpanel Expert

Software Engineer, Python, Kubernetes, AI/ML