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Thinking Machines LabThinking Machines LabSan Francisco, CA

Software Engineer, Data Infrastructure

Builds and scales data infrastructure for distributed training pipelines, multimodal data catalogs, and petabyte-scale processing systems. Collaborates with researchers using distributed systems like Spark, Ray, Kafka, and cloud data architectures. Requires backend proficiency in Python/Rust and bachelor's in CS/engineering.

350k – 475k/yr
On-siteData Engineering

About the role

What You’ll Do

  • Design, build, and operate scalable, fault-tolerant infrastructure for LLM Research: distributed compute, data orchestration, and storage across modalities.
  • Develop high-throughput systems for data ingestion, processing, and transformation — including training data catalogs, deduplication, quality checks, and search.
  • Build systems for traceability, reproducibility, and robust quality control at every stage of the data lifecycle.
  • Implement and maintain monitoring and alerting to support platform reliability and performance.
  • Collaborate with research teams to unlock new features, improve data quality, and accelerate training cycles.

Skills and Qualifications

Minimum qualifications:

  • Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
  • Proficiency in at least one backend language (we use Python or Rust).
  • Are fluent in distributed compute frameworks such as Apache Spark or Ray.
  • Are deeply familiar with cloud infrastructure, data lake architectures, and batch and streaming pipelines.
  • Comfort operating across the stack and owning projects end-to-end.
  • Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
  • A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.

Preferred qualifications:

  • Have hands-on experience with Kafka, dbt, Terraform, and Airflow.
  • Have experience building a web crawler.
  • Have extensive experience understanding and scaling deduplication, data mining, and search.
  • Have strong knowledge of file formats and storage systems (e.g., Parquet, Delta Lake, etc.) and how they impact performance and scalability.
  • Are proactive about documentation, testing, and empowering your teammates with good tooling.

Logistics

Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD. Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

Skills

PythonRustSparkRayKafkadbtTerraformAirflowDelta LakeParquet
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