Loop

Machine Learning Engineer

Austin, Texas, United States

Not SpecifiedCompensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Data, E-commerce, BiotechnologyIndustries

Machine Learning Engineer

Employment Type: Full-time


About the Data Organization

The Data team at Loop is on a mission to empower merchants with transformative data products that drive success beyond returns. By building tools that merchants love and fostering a robust data culture, the team enables smarter decision-making across the board. Whether creating insights to guide merchants’ strategies or strengthening internal data-driven processes, the Data team is integral to shaping Loop’s future and unlocking new opportunities for our merchants and teams alike.


About the Role

As a Machine Learning Engineer at Loop, you’ll help turn advanced data capabilities into products that make it easier for merchants to run and grow their businesses. You’ll collaborate closely with the rest of the Data team, Software Engineers, and Product Managers to explore ideas, prototype solutions, and ship machine learning systems that make our merchants’ workflows more efficient, shopper experiences more seamless, and Loop’s products more intelligent. Whether supporting a model already in production or helping design something new, your work will help unlock value for merchants in moments that matter. This is a hands-on, high-impact role where you’ll grow your skills while contributing meaningfully to the future of Loop’s product experience.


Our Blended Work Environment

At Loop, we’re intentional about the way we work so that we can do our best work. We call this our Blended Working Environment. We work from our HQ in Columbus, OH, or one of our Hub or Secluded locations, and are distributed throughout the United States, select Canadian provinces, and the United Kingdom. For this position, we’re looking for someone to join us in Columbus, OH; Chicago, IL; Austin, TX; or Los Angeles, CA.


Our Tech Stack

For ML model development and deployment, we use the AWS ML ecosystem, Airflow, Kubernetes, and Fast API, among other tools. Our backend data infrastructure is supported by Fivetran, dbt, Snowflake, Hex, Secoda, GoodData.


What You’ll Do

  • Work collaboratively with cross-functional partners, including software engineers, product managers, operations, and the rest of the Data team, to scope ML use cases, refine model requirements, and support delivery of features that drive merchant value.
  • Support the development and deployment of ML solutions, contributing to model training, evaluation, and iteration with guidance from more senior team members.
  • Help design and maintain data pipelines and infrastructure that support reliable, scalable ML systems.
  • Contribute to the way we build responsibly with machine learning at Loop, contributing to best practices, tools, and lightweight processes that expand our capabilities.
  • Stay curious and engaged with the broader ML community to continue growing your skills and bringing new ideas into the team.

Your Experience

  • 5–8 years of experience since completing your undergraduate studies; we welcome candidates with advanced degrees (like a PhD) and those with nontraditional paths who’ve gained equivalent experience through hands-on work.
  • 2-3 years of experience as an ML engineer, data scientist, applied scientist, or other applied ML practitioner in a production environment.
  • Proficient in Python and familiar with ML libraries such as Scikit-Learn, PyTorch, or TensorFlow.
  • Solid understanding of classical ML techniques such as regression, classification, clustering, and time series modeling, as well as deep learning frameworks such as CNNs, RNNs, GNNs, and transformers.
  • Familiarity with deploying models into production and monitoring performance over time, even if not the lead on those systems.
  • Comfortable writing production-quality code and querying data with SQL.
  • Excellent communication skills, especially when collaborating across functions or explaining technical concepts to non-technical stakeholders.
  • An interest in ethical ML practices and a thoughtful approach to building systems.

Skills

Machine Learning
AWS ML ecosystem
Airflow
Kubernetes
FastAPI
Fivetran
dbt
Data Products
Data Infrastructure
Model Development
Model Deployment
Prototyping
ML Systems

Loop

Simplifies payments with advanced technology.

About Loop

The company's main product simplifies payments in a complex industry, utilizing advanced technologies to streamline the process.

San Francisco, CaliforniaHeadquarters
2021Year Founded
$63.2MTotal Funding
SERIES_BCompany Stage
Data & Analytics, Automotive & Transportation, Enterprise SoftwareIndustries
11-50Employees

Benefits

Health Insurance
Dental Insurance
Vision Insurance
401(k) Retirement Plan
Unlimited Paid Time Off
Professional Development Budget
Physical and Mental fitness subsidies
Commuter Benefits

Risks

Increased competition may pressure Loop's market share and pricing.
Regulatory changes in Saudi Arabia could impact Loop's operations.
Cybersecurity threats pose risks to Loop's reputation and customer trust.

Differentiation

Loop's platform streamlines shipment document capture and invoice matching efficiently.
Partnerships with major players like J.P. Morgan enhance Loop's market credibility.
Loop's expansion into Saudi Arabia showcases its global reach and adaptability.

Upsides

AI integration boosts Loop's invoice matching accuracy and fraud detection.
Blockchain technology offers Loop enhanced transparency and security in payments.
IoT growth allows Loop to provide real-time tracking and analytics services.

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