Applied AI Engineer

Notchbit; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Notchbit is seeking a machine learning systems engineer to connect research with production software. You will help turn experimental models into dependable runtime behavior for perception and decision-making, balancing performance with safety and observability.

You will collaborate with systems engineers to account for deployment constraints and improve inference paths to meet latency targets, contributing to robust, scalable ML deployments across edge and cloud environments.

Qualifications

• Experience shipping machine learning systems beyond notebook-based experiments.
• Clear communication with cross-functional partners.

Responsibilities

• Integrate and evaluate models used for perception and decision-making.
• Improve inference paths to meet latency and safety needs and support observability.
• Work with systems engineers to account for deployment constraints.

Skills

Shipping ML systems

Clear communication

Job description

Role overview

Connect machine learning research with production software by turning experimental models into dependable runtime behavior. The role focuses on integrating and evaluating models for perception and decision-making, then adapting their inference paths to practical system constraints.

Responsibilities

• Integrate and evaluate models used for perception and decision-making.
• Improve inference paths to meet latency and safety needs and support observability.
• Work with systems engineers to account for deployment constraints.

Requirements

• Experience shipping machine learning systems beyond notebook-based experiments.
• Clear communication with cross-functional partners.

Nice to have

• Familiarity with edge computing or robotics constraints.