Intel Senior Engineer ML Ops/DevSecOps 

United States, California 

847450626

Key Responsibilities:

ML Ops:

• Develop scalable and reliable ML infrastructure.

• Automate ML model deployment, monitoring, and management.

• Implement best practices for data versioning, model training, and experimentation.

• Collaborate with engineers to streamline the ML workflow.

• Enhance model reproducibility and performance.

DevSecOps:

• Integrate security measures into the CI/CD pipeline.

• Conduct security audits and vulnerability assessments.

• Utilize tools for static code analysis, SAST, and Trivy.

• Implement and enforce security standards across development teams.

• Develop and maintain dashboards for monitoring pipeline health and security metrics.

CI/CD:

• Design and maintain robust CI/CD pipelines.

• Optimize build processes for enhanced efficiency.

• Implement strategies for Continuous Build and Test.

• Automate testing, deployment, and monitoring using GitHub Actions.

• Analyze and improve pipeline performance metrics.

Collaboration and Communication:

• Work closely with cross-functional teams to fulfill their requirements.

• Mentor junior engineers and contribute to their professional growth.

• Participate in architecture reviews with a focus on security and performance.

• Effectively communicate project status, risks, and metrics.

Project Management:

• Plan and schedule the development and implementation of multiple long-term and complex projects, often requiring consultative direction.

Problem Solving:

• Utilize extensive expertise to resolve significant issues or analyze unique problems requiring evaluation of intangibles and design innovative solutions.

Decision Making:

• Make consistent decisions regarding the overall goals and objectives of significant programs or segments of the organization.

Organizational Representation:

• Serve as the primary contact on projects, interacting with senior internal and external personnel on complex or widespread issues requiring coordination across organizational lines.

Strong problem-solving, attention to detail, communication, and teamwork skills is also required.

You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.

Minimum Qualifications

6+ years of experience -OR- a Master’s Degreein a STEM related fieldand 4+ years of experience -OR- a PhD in a STEM related field with 2+ years experience in:

• MLOps or DevOps or DevSecOps roles.

• Python/Java, or Go.

• CI/CD tools like GitHub ActionsorJenkins,orequivalent.

• Docker, Kubernetes,AWS/Azure or equivalent.

• Machine learning frameworks and libraries.

Preferred Qualifications

• Infrastructure as Code (IaC) tools like Ansible, BiCep.

• Monitoring and logging tools.

• Regulatory requirements and compliance.

• Certifications such as Certified Kubernetes Administrator (CKA), AWS/Azure Certified DevOps Engineer, or similar.

• Familiarity with tools and practices for deploying and managing ML models in production environments.

• Experience with advanced security frameworks or certifications and disaster recovery strategies.

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock, bonuses, as well as, benefit programs which include health, retirement, and vacation. Find more information about all of our Amazing BenefitsAnnual Salary Range for jobs which could be performed in US, California: $144,501.00-$217,311.00
*Salary range dependent on a number of factors including location and experience