Sr. Machine Learning Engineer
Artificial Intelligence
Automation
Big Data
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Cloud
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Data Engineer
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Machine Learning Engineer
Ml Ops
Platform Engineering
Job Description
CrowdStrike is hiring a Sr. Machine Learning Engineer to join the AIDR Engineering Team, supporting the delivery of high-throughput, low-latency LLM inferencing along with LLM post-training and data engineering. This remote role emphasizes scalable, customer-facing execution with strong engineering practices, autonomy, and continuous improvement.
In this position, you will help turn fast-moving research into production systems, maintain data pipelines that support custom model training and deployment, and work across teams to design solutions that improve performance, reliability, and customer outcomes.
Responsibilities
- Innovate with current machine learning technologies to accelerate data science efforts
- Provide pragmatic engineering support for fast-moving R&D teams
- Build and maintain high-quality solutions for customer-facing applications at scale
- Perform in-depth analysis to identify potential vulnerabilities or gaps
- Construct and maintain data pipelines, including contributing to the training and implementation of custom models
- Collaborate with cross-functional teams to brainstorm, define, and devise solutions
- Commit to ongoing learning and self-improvement
- Stay aligned with customer challenges and continually look for ways to improve support
- Maintain top-tier coding quality through best practices, rigorous testing, and thorough logging and metrics
- Work effectively in a collaborative, agile environment
- Mentor other engineers across a range of technologies and absorb knowledge from peers
- Continuously explore improvements to product architecture, knowledge models, user experience, performance, and reliability
- Own work end to end with autonomy: develop, test, deploy, and monitor changes
- Thrive in an environment that values trust
Requirements
- Prior 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
- Team player mindset
- Strong command of engineering best practices, including effective testing approaches, resilient architecture, and peer code reviews
- Ability to thrive in a test-driven, collaborative, iterative programming environment
- Ability to meet commitments on time while producing unit-tested, code-reviewed software and regularly checking in for continuous integration
- Proven experience applying AI to improve decision-making, streamline workflows, increase efficiency, and drive business outcomes
Technologies
- Python
- Docker
- Kubernetes
- AWS
- GCP
- MaaS
- Kafka
- Cassandra
- Spark
- ElasticSearch
- Terraform
- Chef
- Ansible
Bonus Points
- Existing, demonstrable applied work in scalable architectures for LLM post-training or fine-tuning
- Prior experience in cybersecurity or intelligence fields
Benefits
- Market leader compensation and equity awards
- Comprehensive physical and mental wellness programs
- Competitive vacation and holidays
- Paid parental and adoption leaves
- Professional development opportunities for employees at all levels
- Employee Networks, geographic neighborhood groups, and volunteer opportunities
- Vibrant office culture with world class amenities
- Great Place to Work Certified™ across the globe
- Health insurance
- 401k
- Paid time off
Tech Stack (Not Mandatory to Know Everything)
- High-level coding language such as JVM technologies or Python
- Docker
- Kubernetes
- AWS, GCP, or MaaS
- Kafka, Cassandra, and Spark
- ElasticSearch
- Terraform, Chef, or Ansible
- Experience scaling inference across GPUs or GPU clusters
Location: Remote (remote). Salary: USD 140,000 - 215,000 per year.