Lead Machine Learning Developer

Arctic Wolf, with its unicorn valuation, is the leader in security operations in an exciting and fast-growing industry—cybersecurity. We have won countless awards for our excellence in security operations and remain dedicated to providing an industry-leading customer and employee experience.

Our mission is simple: End Cyber Risk. We’re looking for a Lead Machine Learning Developer to be a part of making this happen.

Lead ML Developer

The Lead ML Developer will be responsible for the design and development of complex and exciting platforms in our Arctic Wolf Labs department. They will drive the technical roadmap of the AI/ML platforms at Arctic Wolf and enable the AI/ML teams to contribute to our Security Research and Threat Intelligence products and initiatives, and will develop cutting-edge systems, services, and frameworks for Arctic Wolf Labs. We are looking for a developer with a strong foundation of AI/ML concepts and workflows to join our pack, support a practice that will continuously evolve and expand the capabilities of our data science team, and contribute to our security products and services.

Arctic Wolf Labs is the research-focused division at Arctic Wolf focused on advancing innovation in the field of security operations. The mission of Arctic Wolf Labs is to develop cutting-edge technology and tools that are designed to enhance the company’s core mission to end cyber risk, while also bringing comprehensive security intelligence to Arctic Wolf’s customer base and the security community-at-large. Leveraging the more than six trillion security events the Arctic Wolf Security Operations Cloud ingests, parses, enriches, and analyzes each week, Arctic Wolf Labs is responsible for performing threat research on new and emerging adversaries, developing advanced threat detection models, and driving improvement in the speed, scale, and detection abilities of Arctic Wolf’s solution offerings. The Arctic Wolf Labs team comprises security and threat intelligence researchers, data scientists, security development engineers with deep domain knowledge in artificial intelligence (AI), security R&D, as well as advanced threat offensive and defensive methods and technologies. Security Research Services Development partners with these groups to understand requirements, design & implement scalable, fault-tolerant solutions, and build the next generation of security capabilities for Arctic Wolf.

AS A LEAD ML DEVELOPER AT ARCTIC WOLF, YOU WILL:

· Support R&D of distributed, highly scalable, and fault-tolerant microservices

· Use test-driven development techniques to develop beautiful, efficient, and secure code

· Create and scale high-performance services that bring new capabilities to Arctic Wolf’s data science organizations

· Execute on deliverables on the roadmap of ML engineering, modeling, and operations at Arctic Wolf

· Influence the work of team members, and mentor emerging technical leaders.

· Develop trusted cross-team relationships to deliver solutions that span multiple areas of expertise

· Identify problems proactively and propose novel solutions to solve them

· Continuously learn and expand your technical horizons

WE’RE LOOKING FOR SOMEONE WHO:

· Will collaborate closely with our data science and ML teams across different cybersecurity domains to define ML infrastructure requirements and build critical data services

· Can leverage MLOps best practices to design and develop scalable model training, evaluation, experimentation and deployment workflows

· Has extensive experience in ML training (local and distributed), feature extraction, dataset creation

· Is comfortable deploying software with CI / CD tools including Jenkins, Harness, Terraform etc.

· Is an expert at developing and deploying assets in the cloud - preferably AWS and Kubernetes using IAC (infrastructure as code)

· Can build a workflow orchestration platform to be used by other developers

· Has hands-on experience of 2+ years implementing data pipeline infrastructure for data ingestion and transformation near real-time availability of data for applications and ML pipelines

· Has experience designing optimized solutions for ingestion, curation of large datasets

· Has working knowledge of Data Lake technologies, data storage formats (Parquet, ORC, Avro), and query engines (Athena, Presto, Dremio) and associated concepts for building optimized solutions at scale

· Maintains a proficient level in one of the following programming languages or similar- Python, Java, Go

· Has experience with data pipelines tools (Flink, Spark or Ray) and orchestration tools such as Airflow, Dagster or Step Functions

· Is an expert in implementing data streaming and event-based data solutions (Kafka, Kinesis, SQS/SNS or the like)