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Manager, Applied Research & Engineering - AI Security

Relyance
Relyance
Company Website Link
Remote Job Type
Full Time
Remote Job Location
United States (Remote)
Remote Job Experience
5+ years
Remote Job Salary Range
$210,000 - $260,000
Key Skills:
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Job Description

As Relyance AI’s Manager, Applied Research & Engineering - AI Security, you will lead the delivery of our next-generation AI Security product and then lead a global team continuing to build out the offering. You will be responsible for the technical vision, strategy, and execution of critical software initiatives that are the future of Relyance AI.

As a Manager, Applied Research & Engineering, your role will include:


- Technical Strategy & Architecture: Define the long-term technical vision and architecture for AI security products, ensuring solutions are scalable, performant, and built for high-assurance security standards.
- Applied Research & Development: Drive a culture of applied research and threat modeling, translating complex findings around model vulnerabilities (e.g., adversarial attacks, data poisoning) into tangible, deployable product features.
- Security Engineering Excellence: Oversee the design, development, and deployment of solutions for AI/ML systems, focusing on runtime protection, data lineage, and privacy-preserving techniques.
- Leadership & Team Building: Serve as an inspiring, hands-on leader for a global, geographically dispersed team. Recruit, hire, mentor, and coach top-tier security and AI engineering talent, fostering a culture of innovation, urgency, and technical ownership.
- Cross-Functional Execution: Work closely with Product Management to define the product roadmap and translate AI security research findings into commercially viable product features.

This role could be a fit for you if you bring:


- 5+ years of experience in Deep Learning Research, focusing on large-scale model training (e.g., LLMs, Generative Models) in industry or a top-tier academic/research lab.
- Deep, hands-on expertise in the entire model lifecycle: From custom data collection/curation to pre-training, post-training alignment (fine-tuning/RLHF), and deployment of specialized models.
- A self-directed, intellectually curious mindset and comfort leading ambiguous projects from 0→1.
- A strong passion for exploring the limits of AI and a belief in creating machine learning systems to inform strategic decisions in fast-moving environments.
- Extensive experience working with large, complex proprietary datasets for novel model training, coupled with exceptional scientific communication skills to clearly articulate complex theoretical concepts and research directions to both technical and executive audiences.
- Expert-level proficiency in Python and modern ML frameworks (PyTorch, JAX, or TensorFlow).
Bonus Points
- PhD in Computer Science, Machine Learning, or a related quantitative field.
- Prior experience applying foundational models specifically to security, threat intelligence, or advanced data privacy challenges.
- Experience in AI/ML product development and deployment in a startup environment.
- Experience leading research teams and defining scientific roadmaps that resulted in significant model breakthroughs or publications.

Working at Relyance AI

At Relyance AI, we create an unreasonably hospitable and data-driven culture. We prioritize exceeding customer, and each other’s, expectations in every interaction. This means empowered team members solving problems proactively based on information, crafting personalized experiences, and radiating enthusiasm. Behind the scenes, trust and freedom allow team members to find creative solutions, while shared purpose and recognition fuel a spirit of greatness to truly wow customers and each other. We deconstruct failures to learn from them and take great pride in our successes; celebrating both.

Relyance AI is proud to be an equal-opportunity employer. We celebrate representation and are committed to creating an inclusive environment for all employees. We are committed to fair and equitable compensation practices. We use data-driven pay practices with the goal of ensuring offerings are competitive to the market and our team members are being compensated correctly based on their roles, experience, and location. As such, the base salary pay range for this role is $210,000 - $260,000.

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