AI/ML Platform Engineer: Scalable Inference & Training

Whatnot; New York (NY); On-site; USD 200,000 - 345,000; Full time

Benefits offered by this job

Flexible time off

Health Insurance

Home office setup allowance

Monthly cell phone and internet

Wellness allowance

Childcare allowance

Family planning support

401k employer match

Job summary

Whatnot is seeking an AI/ML Platform Engineer to design and scale the core infrastructure powering machine-learning applications across the company. You’ll work closely with ML scientists to bring cutting-edge models into production and enhance product experiences.

You will build systems for low-latency, high-throughput inference, distributed training pipelines, and GPU utilization, enabling Whatnot’s AI initiatives at scale.

Qualifications

• Bachelor’s degree or equivalent work experience in CS/Math/Stats.
• 1+ years of professional Python development.
• Experience building production ML systems and scalable infrastructure.
• Strong written and verbal communication; ability to collaborate remotely.

Responsibilities

• Own infrastructure powering AI/ML models across critical surfaces (growth, recommendations, trust & safety, fraud, seller tooling).
• Prototype and productionize novel ML architectures shaping user experience and marketplace dynamics.
• Design and scale inference infrastructure for low latency and high throughput.
• Build distributed training and inference pipelines leveraging GPUs and data/model parallelism.
• Take on new technical challenges as Whatnot scales AI.

Skills

Python

Production systems experience

Communication

Remote collaboration

Education

Bachelor’s degree in Computer Science, Statistics, Applied Mathematics or related field

Equivalent work experience

Tools

PostgreSQL

DynamoDB

Elasticsearch

Redis

DataDog

Grafana

AWS SageMaker

Lambda

Kinesis

S3

EC2

EKS/ECS

Apache Kafka

Flink

Job description

Whatnot is seeking an AI/ML Platform Engineer to design and scale the core infrastructure powering machine-learning applications across the company. You’ll work closely with ML scientists to bring cutting-edge models into production and enhance product experiences.

You will build systems for low-latency, high-throughput inference, distributed training pipelines, and GPU utilization, enabling Whatnot’s AI initiatives at scale.