Senior Machine Learning Engineer

CrowdStrike

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
CA
Salary
$140,000–$215,000 / yr
Posted
2 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $226k
This role $178k
$123k most similar roles pay here $294k

This role pays less than 83% of similar roles. Most pay $197,631–$254,750 — the shaded band above. At the midpoint, this role pays about $178k versus about $226k for comparable roles.

Based on 240 similar postings.

Employer

About CrowdStrike

CrowdStrike is a leading American cybersecurity technology firm, specializing in cloud-native endpoint protection, threat intelligence, and incident response.

CrowdStrike currently has 28 open roles on FindRole.

Listed pay typically runs $140,000–$215,000 across 28 roles with salary data.

Most-posted roles

View all roles at CrowdStrike

At a glance

TL;DR · Senior Machine Learning Engineer

The Sr. Machine Learning Engineer joins the AIDR Engineering Team to provide engineering support and solutions for a data science group focused on high-throughput, low-latency LLM inferencing. This role involves supporting LLM post-training, constructing and maintaining data pipelines, and contributing to the training and implementation of custom models. The engineer will work to ensure enterprise users can interact safely with AI applications while ensuring high-quality code through rigorous testing and monitoring. Key technologies include Python or JVM languages, Docker, Kubernetes, AWS, GCP, MaaS, Kafka, Cassandra, Spark, ElasticSearch, Terraform, Chef, and Ansible. Candidates must possess expertise in scaling inference across GPU clusters, distributed systems, and LLM post-training methods. The role addresses the technical challenge of building scalable architectures for large language models within a complex data environment.

What does a Machine Learning Engineer earn in California?

Median $246394 from 172 postings across 28 companies.

See salary data

What you'll do

  • Provide engineering support for high-throughput, low-latency LLM inferencing and post-training.
  • Construct and maintain data pipelines aligned to rigorous evaluation standards.
  • Implement high-quality solutions for customer-facing applications at scale.
  • Identify potential vulnerabilities or gaps through in-depth analysis of systems.
  • Develop, test, deploy, and monitor changes autonomously from end to end.
  • Refine product architecture, knowledge models, performance, and reliability.
  • Mentor fellow engineers while actively absorbing knowledge across various technologies.

What we're looking for

  • Experience in data engineering and architecture supporting advanced data science use cases.
  • Deep understanding of LLM post-training methods and computational architectures.
  • Understanding of scalability and distributed systems, including sharding, partitioning, and concurrency.
  • Proven experience utilizing AI technologies to enhance decision-making and streamline workflows.
  • Proficiency in high-level coding languages such as Python or JVM technologies.
  • Experience scaling inference across GPUs or GPU clusters.
  • Knowledge of infrastructure tools like Docker, Kubernetes, AWS, GCP, Kafka, Cassandra, Spark, or Terraform.
  • Ability to work in a test-driven, collaborative environment following engineering best practices and peer code reviews.

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