Machine Learning Engineer I (US)

Payscale

9d•Remote

About The Position

We’re looking for an early-career Machine Learning Engineer to help take models built by our Data Science team and turn them into reliable, production-ready services. As a member of our Data Engineering team, you will play a critical role in reviewing, optimizing, and deploying AI/ML models into production environments. You’ll work alongside experienced engineers and data scientists, contributing to model packaging, training, deployment, integration, testing, and monitoring—while growing your MLOps and software engineering skills.

Requirements

Bachelor's or master's degree in Computer Science, Engineering, or related field.
1+ years of experience (including internships/co-ops) building software in a production environment.
Proficiency in Python with a focus on readable, testable code.
Familiarity with core ML concepts and at least one ML framework (e.g., PyTorch, TensorFlow, scikit-learn).
Familiarity with building or consuming APIs (HTTP/JSON) and basic service development patterns.
Comfort working in a collaborative environment: asking questions, communicating tradeoffs, and incorporating feedback.
Willingness to learn cloud, containerization, and MLOps practices as part of day-to-day work.

Nice To Haves

Exposure to MLOps tools or patterns (e.g., MLflow, Airflow, Kubeflow, feature stores, model registries).
Experience with containers (Docker) and/or orchestration (Kubernetes).
Experience with observability tools (e.g., Datadog, Prometheus/Grafana) and production troubleshooting.
Basic performance tuning experience (profiling, async patterns, caching concepts).
Experience working with data platforms (e.g., Snowflake, Spark) or large-scale data pipelines.

Responsibilities

Partner with Data Science to package models for deployment and integrate them into our products and internal services.
Implement and improve ML deployment and inference workflows (batch and/or real-time), including automation and CI/CD patterns with guidance from senior engineers.
Build and maintain API endpoints or services that expose model predictions, including input validation, error handling, and documentation.
Write tests (unit/performance/integration) to validate model behavior and service reliability; help create repeatable validation checks and release processes.
Instrument services with logging/metrics and help monitor production behavior; participate in incident triage and troubleshooting with support from the team.
Contribute to performance and cost improvements through profiling and practical techniques like batching, basic caching, and efficiency-minded design.
Stay current on relevant AI/ML engineering best practices and share learnings with the team.

Benefits

All around awesome culture where together we strive to live our 5 values:
Data informed decision making.
Customer first. Always.
Succeed together.
Relentless about results. Obsessed with excellence.
Lead the change. Shape the standard.
An open and inclusive environment where you’ll learn and grow through programs and resources like:
Monthly company All Hands meetings
Regular opportunities for executive leadership exposure through things like AMAs
Access to continued learning & development opportunities
Our commitment to a continuous feedback culture which allows us to drive performance and career growth
A growing network of Employee Resource Groups
Company sponsored volunteer hours
And more!
Our more standard benefits
Flexible paid time off, giving you the opportunity to rest, relax and recharge away from work
14 Paid Company Holidays, includes 2 floating holidays (you choose!)
A comprehensive benefits plan including medical, dental, life, vision, disability, and life insurance covered up to 100% by Payscale
Unlimited infertility coverage benefits through our medical plans
Additional supplemental health benefits offered to you and your family
401(k) retirement program with a fully vested immediate company match
16 weeks of paid parental leave for birthing and non-birthing parents
Health Savings Account (HSA) options and company contributions each pay period
Flexible Spending Account (FSA) options for pre-tax employee allocations
Annual remote work stipend to be used on wellness or home office equipment