Principal Site Reliability Engineer, SecurityScorecard
Cybersecurity ratings & risk management
Be an early applicant
Cybersecurity ratings & risk management
501-1000 employees
Be an early applicant
501-1000 employees
Company mission
SecurityScorecard's mission is to make the world a safer place by transforming the way organizations understand, mitigate, and communicate cybersecurity risk to their boards, employees, and vendors.
Role
Who you are
- 6+ years in SRE, DevOps, or infrastructure roles, including 2+ years supporting machine learning or data-intensive workloads in production
- Deep experience running Kubernetes in production, especially with ML workloads (GPU scheduling, autoscaling, pod optimization)
- Proven track record building CI/CD pipelines for ML systems using tools like GitHub Actions, GitLab CI, or Jenkins
- Strong command of cloud-native infrastructure (EKS, GKE, or AKS), including GPU provisioning and autoscaling for AI workloads
- Familiarity with MLOps and workflow orchestration tools, such as MLflow, Kubeflow, Airflow, and Argo Workflows
- Proficiency in Infrastructure as Code and GitOps with Terraform, Helm, and Argo CD
- Experience managing event streaming (Kafka), distributed databases (YugabyteDB), and LLM observability (Langsmith / Langfuse)
- Programming/scripting ability in Python, Go, or Bash for automating infrastructure or ML pipelines
- Solid knowledge of monitoring and observability tools (Prometheus, OpenTelemetry, New Relic, Datadog)
- Strong communication and mentoring skills; able to influence cross-functional teams
What the job involves
- As a Principal Site Reliability Engineer (SRE) focused on ML and AI initiatives, you will play a critical role in designing and scaling infrastructure that powers advanced machine learning workloads
- You will lead the development of highly reliable, observable, and automated Kubernetes-based platforms that support model training, inference, and continuous delivery of ML applications
- Working closely with ML engineers, data scientists, and platform teams, you will help operationalize machine learning workflows and bring cutting-edge AI capabilities into production with confidence and speed
- Design and scale Kubernetes infrastructure purpose-built for ML/AI workloads, including GPU scheduling, autoscaling, and secure multi-tenant clusters
- Enhance CI/CD pipelines for ML applications and model delivery (MLOps), including support for reproducible training, model versioning, and shadow testing
- Implement progressive delivery strategies (e.g., canary, A/B testing) for machine learning models to ensure safe and incremental rollout of experiments
- Partner with ML teams to operationalize ML workflows with tools like MLflow, Kubeflow, or Vertex AI, and integrate these into the broader platform architecture
- Integrate and support Apache Kafka for streaming data ingestion and real-time feature delivery for ML pipelines
- Deploy and maintain Airflow pipelines for orchestrating complex ML workflows and data preparation tasks
- Build and optimize infrastructure and workflows for Langsmith/Langfuse to support observability and tracing of LLM-based applications and agents in production
- Lead improvements in Infrastructure as Code using Terraform, Helm, and Argo CD, while establishing reusable and secure infrastructure patterns for AI applications
- Support YugabyteDB as a high-performance, distributed database backend for ML and AI services requiring strong consistency and scale
- Define and enforce automated testing strategies tailored to ML environments, such as data validation, model performance regression, and pipeline integration tests
- Drive observability and alerting across ML pipelines and services, including monitoring data drift, model latency, and system-level metrics using tools like Prometheus, OpenTelemetry, New Relic, and Datadog
- Actively support incident response for ML systems and infrastructure, focusing on root cause analysis and resilient remediation strategies
- Mentor engineers and champion best practices across ML, platform, and infrastructure teams
Our take
Organizations understand the value of data and the value of business partnerships that will help them leverage it. However, involving more companies increases the risk of vulnerabilities, and therefore costly data breaches. SecurityScorecard is a cloud-based enterprise SaaS solution that helps organizations assess and manage cybersecurity risks, offering analyses of potential partner companies using A-F security ratings.
SecurityScorecard looms over its competitors as it covers millions of companies, offering near-instant cybersecurity analyses and an array of capabilities. It has a large, global, and big-name customer base, including 9 of the top 10 pharmaceutical companies and 9 of the top 10 banking institutions, and it is likely to go public in the next few years.
It has both developed and consolidated an impressive lead in a sector that will continue growing and rewarding cutting-edge security solutions. It looks set to remain an industry leader with demonstrable, accessible, and highly attractive customer offerings. In 2024, this included a supply chain cyber risk management platform - MAX - which is driving record revenue.
Freddie
Company Specialist at Welcome to the Jungle
Insights
62% employee growth in 12 months
Company
Funding (last 2 of 7 rounds)
Mar 2021
$180m
SERIES E
Jun 2019
$50m
SERIES D
Total funding: $294.4m
Company benefits
- Stock options
- 12 weeks of paid maternity leave / 4 weeks paid paternity leave
- Work from home opportunities
- Medical, dental, and vision coverage
- Unlimited PTO
- 401K
- $3k annual education stipend per employee
- Full access to our learning platform and company professional development events
- Up to $10K referral bonus
Company HQ
Midtown South, New York, NY
Leadership
Aleksandr Yampolskiy
(CEO)Worked at Oracle and Goldman Sachs, before serving for 2 years as CISO of Gilt Group. Founded NYC Technology Startup, Meetup, in 2012 and then worked as CTO of Cinchcast.
Sam Kassoumeh
(COO)Progressed from Technology Compliance Manager to Head of Security and Compliance at Gilt Groupe within 4 years, and worked as Cyber Security Advisor for Billy.
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