BJAK

Machine Learning Engineer

• Build core ML systems that power a proactive, long-horizon AI product.
• Own work end-to-end: data preparation, training, evaluation, inference, and iteration.
• Turn research ideas into working systems that run reliably in production.
• Debug model failures and system issues using real production signals.
• Iterate quickly: ship, measure outcomes, refine, and repeat.
• Collaborate closely with research, product, and engineering to deliver real user impact.
• Mentor and review work from other ML engineers through example and technical judgment.
• Work under real production constraints: latency, cost, reliability, and safety

Senior Machine Learning Engineer

• Build core ML systems for proactive AI products
• Own tasks end-to-end from data preparation to iteration
• Collaborate with research and product teams
• Debug and resolve production issues
• Mentor other ML engineers

• Build core ML systems that power a proactive AI product
• Own work end-to-end: data preparation, training, evaluation, inference, and iteration
• Turn research ideas into working systems that run reliably in production
• Collaborate closely with research, product, and engineering teams
• Mentor other ML engineers through example and technical judgment

• Build core ML systems for a proactive AI product
• Own work end-to-end: data preparation, training, evaluation, inference, and iteration
• Turn research ideas into production systems
• Debug model failures using production signals
• Collaborate with research, product, and engineering teams
• Mentor other ML engineers
• Work under production constraints

• Build and improve ML components across data, training, evaluation, and inference.
• Fine-tune and adapt models as part of larger production systems.
• Implement evaluation and testing to understand model behavior.
• Help build and maintain data pipelines for real-world and synthetic data.
• Debug model issues, performance problems, and production incidents.
• Ship improvements iteratively and learn from real user feedback.
• Work closely with senior ML engineers and product teams.
• Work under real production constraints: latency, cost, reliability, and safety.

Member of Technical Staff, Machine Learning

• Build and improve ML components across data, training, evaluation, and inference.
• Fine-tune and adapt models as part of larger production systems.
• Implement evaluation and testing to understand model behavior.
• Help build and maintain data pipelines for real-world and synthetic data.
• Debug model issues, performance problems, and production incidents.
• Ship improvements iteratively and learn from real user feedback.
• Work closely with senior ML engineers and product teams.
• Work under real production constraints: latency, cost, reliability, and safety

Systems Engineer

• Build end-to-end product features across frontend, backend, and AI integrations
• Design agent workflows that handle planning, tool use, failure, and recovery across multiple steps.
• Integrate LLMs, memory, and external tools into systems that behave reliably under real-world conditions
• Design real-time AI interactions with streaming, partial results, and tight latency constraints
• Improve system reliability, observability, and fallback mechanisms
• Collaborate closely with ML, backend, and product teams to ship features end-to-end
• Continuously iterate based on real usage and failure modes

BJAK

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Member of Technical Staff, Machine Learning

Member of Technical Staff, Machine Learning

Member of Technical Staff, Machine Learning

Member of Technical Staff, Machine Learning

Member of Technical Staff, Machine Learning

Member of Technical Staff, Machine Learning

Full Stack Engineer, AI Systems

Full Stack Engineer, AI Systems

Full Stack Engineer, AI Systems

Full Stack Engineer, AI Systems