ML Data Infrastructure Engineer

Description

The company builds advertising technology that helps businesses of every size reach, monetize and grow their audiences worldwide.

You would join the ML Data Platform team, which builds a highly available, globally distributed set of services. Those services support fast development of new systems that plug into the platform and strengthen it.

The team is deliberate about who it hires and how it works together, looking for people who excel individually and also support those around them.

Applicants are asked to submit an application online. The application window is expected to close within 30 days of the posting date. Questions about this posting go to the company's site.

Responsibilities

• Design and build data processing infrastructure for model training and feature serving, with a focus on performance, reproducibility and traceability.
• Work closely with research teams to design and implement new data processing architectures for emerging model and training approaches.
• Find and fix performance bottlenecks across the training data pipeline, from raw ingestion through to feature delivery.
• Set best practices and build tooling for data infrastructure that ML teams across the company use.

Requirements

• You have 1 to 3 years of experience and a BS and/or MS in Computer Science.
• Strong software engineering fundamentals, including experience building high-throughput, fault-tolerant distributed systems.
• Hands-on experience with distributed computing frameworks such as Apache Spark or Flink.
• A solid grasp of data structures, systems design and performance optimization.
• Strong problem-solving skills and close attention to detail.
• Optional: background in MLOps, data infrastructure or ML infrastructure.
• Optional: experience with ML training pipelines, feature stores or model-serving systems.

Conditions

Base pay for this role in California ranges from $140,000 to $250,000 USD.

Total compensation depends on factors including market location, job-related knowledge, skills and experience.

Equity and other incentive compensation may be offered depending on the position.

The company uses technology-assisted tools, including artificial intelligence, to help identify and evaluate candidates, but human reviewers make all hiring decisions.

The company is an equal opportunity employer and considers all applicants regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status, or other legally protected characteristics.

Benefits

• Equity eligibility.
• Medical, dental, vision, life and disability insurance.
• 401(k) retirement plan.
• Unlimited discretionary time off.
• 10 paid holidays per year.
• 80 hours of paid sick leave per year.