• Overseeing fleet maintenance operations across multiple locations • Ensuring vehicle maintenance, repairs, preventive maintenance programs, and fleet compliance requirements are executed safely and efficiently • Providing leadership and oversight of in-house maintenance shops • Managing relationships and performance with third-party maintenance providers • Collaborating with local operations leadership and corporate fleet team for fleet reliability and vehicle availability

The Cloud Data Platform Engineer will play a central role in the deployment, monitoring, and optimization of cloud platforms used by our data scientists. This role requires hands-on expertise in cloud infrastructure, modern DevOps practices, secure data operations, and automation frameworks. You’ll partner closely with data scientists, machine learning engineers, and data engineers to ensure our analytics systems run securely, efficiently, and at scale. You’ll work with our Platform Engineering team to define and implement these patterns so they can be codified and reused across our organization. Location: Remote, preferably US-based Primary Responsibilities Cloud Infrastructure & Operations - Manage, scale, and optimize cloud environments used for data science workloads (primarily AWS, Databricks, dbt). - Provision, maintain, and optimize compute clusters for ML workloads (e.g., Kubernetes, ECS/EKS, Databricks, SageMaker). - Implement and maintain high-availability solutions for mission-critical analytics platforms. - Deep expertise in AWS resource management and provisioning, including IAM roles and permissions. DevOps & Automation - Develop CI/CD pipelines for model deployment, infrastructure-as-code (IaC), and automated testing using industry standard toolchains - Build monitoring, alerting, and logging systems for cloud and ML infrastructure (e.g., Datadog, CloudWatch, Prometheus, Grafana, ELK). - Automate provisioning, configuration, and deployments using tools such as Terraform and CloudFormation, GitHub actions, etc. Data Platform Support - Enable and improve data ingestion, transformation, and model execution workflows through platform capabilities and automation. - Develop and maintain self-service capabilities for data scientists to provision and manage reliable, reproducible environments for research and development. - Collaborate with Data Engineering to maintain integrations between data pipelines and cloud systems. - Share responsibility for provisioning and operating application networking capabilities that support data platforms, including API gateways, CDNs, application load balancers, TLS, and WAFs. Security, Compliance & Governance - Implement and operationalize data science security and compliance controls for data science platforms in alignment with enterprise cloud standards. - Conduct periodic risk assessments,best practice reviews, and remediation efforts to strengthen security and resiliency. - Support secure handling of sensitive financial data. Cross-Functional Collaboration - Partner with data scientists, machine learning engineers, and data engineers to deeply understand and support their needs and workflows within data-driven initiatives. - Serve as a technical advisor on cloud architecture, performance optimization, and production readiness for data and ML platforms. - Adopt and champion Agile, DevOps, and Platform Engineering practices (kanban, scrum, continuous improvement, automation, Everything-as-a-Service) - Demonstrate a strong, proactive focus on serving internal customers, prioritizing user experience, identifying opportunities to leverage automation and self-service to reduce toil and cognitive load for developers and researchers. Requirements Education & Certificates - A bachelor’s degree or higher in a STEM field, required Professional Experience - 5+ years of experience in cloud operations, DevOps, platform engineering, SRE, sysadmin or related roles. - Strong proficiency with at least one major cloud provider (AWS preferred). - Hands-on experience with IaC tools (Terraform, CloudFormation, or similar). - Strong scripting skills (Python, Bash, or PowerShell). - Strong understanding of modern authentication and authorization technologies and secrets management (IAM, OIDC, OAuth2, RBAC, ABAC, privileged access management, JIT authorization, PKI). - Experience with common CI/CD systems (GitHub Actions, Jenkins, GitLab CI, ArgoCD,, or similar). - Familiarity with container orchestration (Docker Compose, EKS/Kubernetes, ECS). - Experience supporting data-intensive or ML workloads. Preferred - Experience in financial services, investment management, or other highly regulated industries. - Knowledge of ML/AI platform tools (Databricks, SageMaker, MLflow, Airflow). - Hands-on experience with AI Engineering and LLMOps tools (LLM observability, eval pipelines, building/supporting agentic workflows) are a huge plus. - Understanding of networking, VPC architectures, and cloud security best practices. - Familiarity with distributed compute frameworks (Spark, Ray, Dask).

• Contributes to setting the performance objectives for own team • Drives initiatives to improve candidate feedback mechanisms • Provides guidance to the team on the design of accurate job descriptions • Partners with industry associations and local networking events • Ensures the implementation of advanced analytics and reporting frameworks • Streamlines recruitment processes for permanent and contingent workers • Leads automation initiatives to reduce manual processes in recruitment

• Define, document, and maintain secure business processes supporting export-controlled and federally funded programs subject to EAR, ITAR, FAR, and DFARS requirements. • Serve as the cross-functional lead for export-controlled and government contract programs, ensuring alignment across Technology, Legal, Sales, Operations, Quality, and Finance. • Embed NIST 800-171 security controls, CMMC practices, and FAR/DFARS cybersecurity requirements (including DFARS 252.204-7012 and related clauses) into operational workflows and policies. • Lead initiatives to develop, maintain, and mature CMMC-aligned systems and processes, including readiness for third-party assessments. • Conduct internal audits, gap assessments, and risk analyses related to export controls, cybersecurity compliance, and federal contract obligations. • Develop and maintain documentation required for government contracts, including SSPs, POA&Ms, policies, and process controls. • Build dashboards and KPIs to monitor compliance health, audit readiness, and continuous improvement initiatives. • Develop and deliver training programs for internal stakeholders and external partners on export-controlled workflows, CMMC requirements, and FAR/DFARS compliance obligations. • Drive continuous improvement initiatives using Lean, Six Sigma, or Agile methodologies to enhance both compliance and operational efficiency. • Lead structured change management efforts to ensure smooth adoption of new security controls, systems, and regulatory requirements. • Contribute to and maintain compliance within the company’s Quality Management System (QMS).