Software Engineer
Role Overview
The Software Engineer at itD Tech will design and scale data pipelines for machine-generated data, focusing on time series, logs, and event streams. This mid to senior-level role involves building reliable Spark and Python workflows, resolving performance bottlenecks, and ensuring data quality for machine learning applications. The hire will significantly impact model training and production systems by enhancing data infrastructure performance.
Perks & Benefits
This position offers a fully remote setup for U.S.-based candidates, with a preference for those aligned with Pacific or Central time zones. Employees benefit from comprehensive medical plans, a 401(k), and paid holidays. The company emphasizes direct W2 employment and is unable to provide sponsorship, fostering a professional environment focused on career growth and collaboration.
Full Job Description
itD is seeking a Software Engineer to design and scale the data pipelines that power next-generation foundation models for machine-generated data, including time series, logs, and large-scale event streams. This role contributes directly to the success of model training and production systems by enabling reliable, high-performance data infrastructure at scale. The ideal candidate will bring deep experience in distributed systems and data engineering, along with a proven track record of delivering scalable, production-ready data pipelines that support machine learning workflows.
Location: Remote (U.S.-based; time zone alignment with Pacific or Central preferred)
We provide comprehensive medical benefits, a 401(k) plan, paid holidays, and more. Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship.
Responsibilities:
- Build and scale distributed data pipelines for large-scale time series, log data, and high-volume event streams.
- Design and maintain reliable, high-performance Spark and Python workflows to support model training datasets.
- Analyze and resolve performance bottlenecks related to latency, memory utilization, data skew, and throughput.
- Improve data quality, validation processes, and reproducibility for machine learning workloads.
- Partner with machine learning engineers and researchers toPlease mention the word **UNDAUNTED** and tag RMmEwMTo0Zjg6MWMxOTpkMTFhOjox when applying to show you read the job post completely (#RMmEwMTo0Zjg6MWMxOTpkMTFhOjox). This is a beta feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.
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