Ai Labelling Jobs in Michigan (NOW HIRING)

Job Family: Software

We are a leading global software company dedicated to the world of computer aided design, 3D modeling and simulation— helping innovative global manufacturers design better products, faster! With the resources of a large company, and the energy of a software start-up, we have fun together while creating a world class software portfolio. Our culture encourages creativity, welcomes fresh thinking, and focuses on growth, so our people, our business, and our customers can achieve their full potential.

Our team is seeking a highly skilled AI Security engineer to focus on hands-on technical implementation of security controls across the AI/ML lifecycle.

Key Responsibilities:

• Securing model pipelines (CI/CD for ML / MLOps).

• Implementing cryptographic mechanisms and access controls to ensure data provenance (e.g., verifying that training data hasn't been tampered with).

• Tracking end-to-end data provenance (where training/RAG data originated, who modified it, and how it was sanitized).

• Ensuring compliance with corporate guidelines on data and AI usage and AI regulations

• Maintaining data lineage documentation, AI model nutrition labels, and data bill of materials (DBOM). Data Bill of Materials (DBOM): Experience establishing Data/Model Cards, AI Nutrition Labels, and Data Bill of Materials to audit training data sources, consent, and licensing.

• Risk Assessment & Auditing: Ability to conduct AI impact assessments (AIIAs), bias audits, and data provenance reviews across complex, multi-source ingestion pipelines.

• AI Vulnerability Testing: Proficiency in threat modeling AI systems and defending against AI-specific attacks (e.g., OWASP Top 10 for LLMs, prompt injection, training data poisoning, model inversion, indirect prompt injection).

• Data Provenance & Versioning Tools: Hands-on experience with data lineage and versioning tools like DVC (Data Version Control), OpenLineage, Apache Atlas, or OpenMetadata.

• Cross-Functional Communication: Proven track record bridging technical engineering teams, legal/compliance departments

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Cybersecurity, Data Science, Information Systems, or a related field (or equivalent hands-on industry experience).

• Domain Knowledge: Deep understanding of the end-to-end Machine Learning Lifecycle (from raw data ingestion and feature engineering to fine-tuning, RAG architecture, and production inference).

Certifications (Desirable):

• Certified Information Systems Security Professional ( CISSP )

• Certified Cloud Security Professional ( CCSP )

• Practical AI/ML security credentials (e.g., specialized cloud AI security tracks from AWS/Azure/GCP).

This is a hybrid role based in Livonia, MI or Milford, OH. Applicants must be based in one of these locations or willing to relocate.

Compensation & Benefits:

The salary range for this position is $109,800 to $197,700 and this role is eligible to earn incentive compensation (5-10%). The actual compensation offered is based on the successful candidate's job-related skills, experience, and relevant education/training. Siemens offers health and wellness benefits to employees; you can access the benefits available in your country via the link: https://jobs.sw.siemens.com/benefits/

Why us?

Working at Siemens Software means flexibility - Choosing between working at home and the office at other times is the norm here. We offer great benefits and rewards, as you'd expect from a world leader in industrial software.

A collection of over 377,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we welcome applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit, and business need. Bring your curiosity and creativity and help us shape tomorrow!

Siemens Software. Transform the Everyday

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#LI-HYBRID

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$109,800 $197,700

Organization: Digital Industries

Job Type: Full-time

Category: Research & Development