Your work will shape GitLab's enterprise security posture in the rapidly growing software supply chain security market. You'll focus on SLSA Level 3 compliance, secrets management, CI/CD security hardening, and the foundations of GitLab's global zero trust architecture.

Some examples of our projects:

• SLSA Level 3 compliance and provenance attestation across GitLab's CI/CD platform
• Integrated secrets management and runner security for container-isolated, secure pipelines

You'll lead the end-to-end software supply chain security architecture for GitLab's CI/CD platform, including SLSA Level 3 implementation and CI infrastructure hardening. You'll drive cross-team technical strategy and decisions across our Software Supply Chain Security (SSCS) stage teams, aligning engineering work to SSCS strategic plans.

You'll collaborate with infrastructure and CI/CD teams to design and land long-term initiatives for secure, scalable runner architecture, container isolation, and pipeline security at scale. You'll propose and validate technical implementations that support architectural changes to improve CI/CD scaling and performance on critical paths.

You'll teach, mentor, and coach Staff Engineers and individual contributors, raising the bar on supply chain threat modeling, secrets management, artifact signing, and SBOM lifecycle practices.

You'll partner with Engineering Managers and senior leadership to define roadmaps, break down complex initiatives, and enable Staff Engineers to lead sub-department-wide efforts.

You'll engage with customers and external stakeholders as a technical consultant and spokesperson for GitLab's software supply chain security capabilities and roadmap.

You'll collaborate with product, security, and compliance stakeholders to ensure features meet enterprise security, governance, and regulatory expectations in the software supply chain security market.

Key responsibilities include:

• Providing architectural leadership across multiple engineering teams
• Shaping GitLab's enterprise security posture in the rapidly growing software supply chain security market
• Focusing on SLSA Level 3 compliance, secrets management, CI/CD security hardening, and the foundations of GitLab's global zero trust architecture

Key requirements include:

• Deep expertise in software supply chain security, including threat modeling for supply chain attack vectors, SLSA implementation and attestation systems, and SBOM generation and lifecycle management
• Strong knowledge of artifact signing and verification using the Sigstore ecosystem, including Cosign, Fulcio, Rekor, and in-toto attestations
• Experience designing and hardening CI/CD security, such as runner isolation, pipeline security controls, and secrets management in large-scale environments

Preferred qualifications include:

• Background in distributed systems and infrastructure, including building resilient CI/CD platforms that process high pipeline volumes and optimizing performance for critical paths
• Practical experience with container security and Kubernetes security, including admission controllers, policy controllers, workload isolation, and registry hardening
• Proficiency in Go or Rust in a production environment, combined with expert-level understanding of CI/CD workflows and DevSecOps best practices
• Experience operating as a Principal or Staff Engineer across multiple development teams, providing architectural leadership and partnering with Engineering Managers and senior leaders
• Demonstrated capacity to clearly communicate complex problems and solutions

Our Software Supply Chain Security stage engineering teams are responsible for authentication and access within GitLab. We also build features that help customers manage vulnerabilities, dependencies, security policies, and compliance frameworks across their organizations.

The base salary range for this role's listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits.

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Cyngn is a publicly-traded autonomous technology company that deploys self-driving industrial vehicles to factories, warehouses, and other facilities throughout North America.

We are a small company with under 100 employees, operating with the energy of a startup. However, we're also publicly traded, which means our employees get access to the liquidity of our publicly-traded equity.

As a Senior DevOps Lead at Cyngn, you will play a vital role in architecting and managing infrastructure across cloud and autonomous vehicle systems. This position combines traditional cloud DevOps leadership with specialized expertise in robotics and autonomous systems infrastructure.

Responsibilities

• Lead and architect cloud and vehicle infrastructure initiatives across AWS and ROS/Linux environments
• Design and implement scalable solutions for both cloud services and autonomous vehicle systems
• Establish and maintain DevOps best practices, CI/CD pipelines, and infrastructure as code
• Drive observability, monitoring, and incident response strategies
• Optimize performance and cost efficiency of cloud and edge computing resources
• Mentor team members and foster a developer-friendly environment
• Manage on-call rotations and incident response processes
• Architect solutions for processing and storing large-scale vehicle telemetry data
• Lead security initiatives and compliance efforts across infrastructure

Requirements

• 10+ years of relevant DevOps/Infrastructure experience
• Proven track record as a technical lead in platform or infrastructure teams
• Advanced expertise in AWS services, infrastructure as code (Terraform), and Kubernetes
• Strong experience with service mesh (Istio) and Helm/Kustomize
• Deep understanding of ROS/ROS2 and Linux kernel configurations
• Experience with GPU configurations and ML infrastructure
• Expertise in ARM and NVIDIA CUDA platform configurations
• Strong programming skills in Python and shell scripting
• Experience with infrastructure automation (Ansible)
• Expertise in CI/CD tools (Jenkins, GitHub Actions)
• Strong system architecture and design skills
• Excellence in technical documentation
• Outstanding problem-solving abilities
• Strong leadership and mentoring capabilities

Nice to haves

• Experience with autonomous vehicle systems
• Track record of optimizing GPU-based ML infrastructure
• Experience with large-scale IoT deployments
• Contributions to open-source projects
• Experience with real-time systems and low-latency requirements
• Expertise in security implementations including SSO, IdP, and AWS Cognito
• Experience with JFrog artifactory and container registry management
• Proficiency in AWS IoT Greengrass
• Experience with container resource management on edge devices
• Understanding of CPU affinity and priority scheduling
• Track record of implementing cost optimization strategies
• Experience with scaling systems both horizontally and vertically

Benefits & Perks

• Health benefits (Medical, Dental, Vision, HSA and FSA (Health & Dependent Daycare), Employee Assistance Program, 1:1 Health Concierge)
• Life, Short-term, and long-term disability insurance (Cyngn funds 100% of premiums)
• Company 401(k)
• Commuter Benefits
• Flexible vacation policy
• Sabbatical leave opportunity after five years with the company
• Paid Parental Leave
• Daily lunches for in-office employees
• Monthly meal and tech allowances for remote employees

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As a Radiologic Technologist, you will conduct routine procedures and tests using radiology equipment to acquire patient diagnostic data. You will prepare for and assist the radiologist in completion of intricate radiographic procedures, including preparation and administration of contrast media and medications in accordance with state and federal regulations.

Responsibilities:

• Demonstrate a thorough knowledge of all aspects of General Diagnostic Radiology, familiar with and adhere to Departmental Protocols and Policy and Procedures of UNC Healthcare System.
• Ensure that patient demographic, emulsion markers, and examination requested are correct, critique, orient and save all pertinent images, transmit QA-ed images to PACS, ensure that all images reach PACS, document completion and/or cancellation of all procedures in RIS.
• Conduct routine procedures and tests using radiology equipment to acquire patient diagnostic data.
• Perform work in a timely manner, perform quality radiographic images on a consistent and on-going basis, analyze request and draw appropriate conclusions for examination and action plan.
• Use RIS, CIS, PACS and SMS effectively and appropriately to access information and document status of procedures.

To be successful in this role, you will need to have an Associate's degree or completion of an accredited Radiologic Sciences Program. You will also need to be Registered by the American Registry of Radiological Sciences or registry eligible and become registered within one (1) year from date of hire.

We offer a competitive salary range of $24.98 - $35.91 per hour, with a standard hours per week of 40.00. This is a full-time position with a day job schedule.

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Founded by British makeup artist and beauty entrepreneur Charlotte Tilbury MBE in 2013, Charlotte Tilbury Beauty has revolutionised the face of the global beauty industry.

The AI & ML Engineering team accelerates the adoption of AI across the business, championing innovation while ensuring our machine learning products are robust, scalable, and cost-efficient.

Responsibilities:

Partner with stakeholders to scope problems and identify the right solution - whether leveraging existing AI tools or building custom workflows & solutions.

Design and implement agentic systems using techniques spanning RAG, grounding, prompt engineering, and orchestration on a GCP-first stack.

Build and maintain production ML pipelines and services for non-GenAI use cases (e.g. recommender systems, customer segmentation models, marketing optimisation modules, leveraging supervised, unsupervised and/or econometric modelling approaches).

Develop APIs and microservices for AI/ML solutions, ensuring security, scalability, and observability.

Implement CI/CD for ML services, writing infrastructure as code, and monitoring for model/data drift and performance.

Establish robust guardrails for safe AI usage, including prompt security, practical evaluation frameworks, and compliance with privacy regulations.

Drive and evangelize best practices, reusable templates, and documentation to scale AI/ML delivery across the business.

Collaborate with data engineers, data scientists, front & back-end engineers, product managers, legal & infosec colleagues to deliver impactful solutions end-to-end.

Who you will work with

The AI & ML Engineer Lead and the wider data team.

About you

The role requires a blend of technical depth and product sense, including:

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

Strong Python engineering skills (FastAPI, testing, typing) and experience with cloud-native development (GCP preferred).

Hands-on experience with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud-native ML platforms (e.g. AWS SageMaker, Azure ML) and agent orchestration frameworks such as LangChain and LangGraph.

Solid understanding of MLOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring.

Proven experience deploying and operating ML systems in production (batch and real-time).

Familiarity with RAG architectures, prompt engineering, and evaluation techniques.

Strong grasp of security, privacy, and governance principles (IAM, secrets, PII handling).

Excellent communication skills and ability to work with non-technical stakeholders.

In addition to the above, we would LOVE if you have:

Experience with vector databases and retrieval strategies.

Knowledge of recommender systems and ranking models.

Familiarity with LLM evaluation tools (e.g., RAGAS, TruLens, LangSmith, Arize).

Exposure to feature stores, data lineage, and observability stacks.

Experience in e-commerce or retail environments.

Demonstrable ability to weigh up build/build/configure decisions in the LLM space.

Why join us?

Be a part of this values driven, high growth, magical journey with an ultimate vision to empower everyone, everywhere to be the best version of themselves.

We’re a hybrid model with flexibility, allowing you to work how best suits you.

25 days holiday (plus bank holidays) with an additional day to celebrate your birthday.

Inclusive parental leave policy that supports all parents and carers throughout their parenting and caring journey.

Financial security and planning with our pension and life assurance for all.

Wellness and social benefits including Medicash, Employee Assist Programs and regular social connects with colleagues.

Bring your furry friend to work with you on our allocated dog friendly days and spaces.

And not to forget our generous product discount and gifting!

At Charlotte Tilbury Beauty, our mission is to empower everybody in the world to be the most beautiful version of themselves.

We celebrate and support this by encouraging and hiring people with diverse backgrounds, cultures, voices, beliefs, and perspectives into our growing global workforce.

By doing so, we better serve our communities, customers, employees - and the candidates that take part in our recruitment process.

If you want to learn more about life at Charlotte Tilbury Beauty please follow our LinkedIn page!

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