Machine Learning Engineer 1 | Careers | Abnormal AI

EducationPals; Dallas (TX); Remote; USD 120,000 - 150,000; Full time

Job summary

Abnormal Innovate in Dallas, TX is seeking a Machine Learning Engineer I to join the Misdirected Email Detection team. You will build and deploy ML models to detect misdirected outbound emails, helping protect customer data at scale while minimizing SOC workload.

This role offers remote options and the chance to work on critical security systems. You will collaborate with cross-functional teams to translate requirements into reliable production features, apply AI fundamentals and machine

Qualifications

• Covered skills: AI fundamentals, Machine learning.

Skills

AI fundamentals

Machine learning

Job description

Join us at Abnormal Innovate on November 5 in Dallas, TX Machine Learning Engineer 1 Remote - SingaporeMessage Security ProductsR-101268 About the Role Abnormal AI is seeking a Machine Learning Engineer - I (MLE) to join the Misdirected Email Detection (MED) team. The MED team plays a critical role in preventing accidental data loss by detecting and blocking misdirected outbound emails, delivering protection at scale without adding operational burden to customer SOCs. [...] The Company may delay

Relevance is based on skills and concepts, not a guarantee that you qualify.

Covered skills: AI fundamentals Machine learning

Skills to close: None listed

Build the skills for this job

Coming-soon courses matched to this posting: outline, waitlist, and skill path.

1. From Prompts to Production Constraints

Understand why single-shot generation fails in real workflows and how constraints enable controllable, reusable outputs.

2. Reference-Based Generation and Identity Preservation

Learn techniques for maintaining visual consistency across outputs using reference images and embeddings.

3. Edit Masking and Spatial Control

Implement region-specific editing that preserves parts of an image while regenerating targeted areas.

4. Style Transfer and Brand Consistency

Build systems that apply and maintain visual style across diverse content while meeting brand guidelines.

5. Structured Outputs and Tool Integration

Generate assets in formats that integrate with design tools, CMSs, and development workflows.

6. Latent Space Manipulation for Advanced Control

Directly manipulate model internals to achieve fine-grained control over generation attributes.

7. Production Pipeline Design and Optimization

Architect end-to-end systems that balance quality, speed, cost, and user experience in real workflows.

Want the full course when it launches? Join the waitlist and we will notify you.

Want the full course when it launches? Join the waitlist and we will notify you.

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