AI & Machine Learning Engineer
Listed on 2026-02-14
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Engineering
AI Engineer
Join a globally recognized leader in entertainment and technology, partnering with Aquent, that is at the forefront of innovation, constantly pushing the boundaries of creativity and technological advancement. This company is dedicated to delivering unparalleled experiences and content that captivate audiences worldwide.
We are seeking a visionary and highly skilled Generative AI & Machine Learning Engineer to join our dynamic team. In this pivotal role, you will be instrumental in shaping the future of interactive content, personalized experiences, and cutting‑edge media creation. Your expertise will directly impact how our audiences engage with our products, bringing imaginative concepts to life through advanced AI and transforming imaginative concepts into tangible, interactive realities.
This role is 100% Remote but candidates must be located near Orlando, FL, Los Angeles, CA, or Seattle, WA.
ResponsibilitiesAs a Generative AI & Machine Learning Engineer, you will be at the heart of our innovation, driving the creation of groundbreaking AI solutions. Your contributions will directly enhance user experiences, streamline content creation, and ensure responsible AI deployment.
- Pioneer Generative Systems: Build sophisticated text-to-image and text-to-video generation systems, alongside advanced speech synthesis and voice cloning models with integrated safety guardrails for authentic character voices.
- Enhance Content Understanding: Develop robust image-to-text and video-to-text systems to power insightful content analysis and improve accessibility.
- Innovate Cross-Modal Experiences: Implement cutting‑edge cross‑modal generation capabilities, such as transforming text and images into video, or audio and text into rich multimedia content.
- Drive Real‑Time Interactions: Create real‑time generative systems that enable dynamic and interactive experiences.
- Ensure Model Quality & Safety: Design and implement custom evaluation models for content assessment, including brand safety, content ratings, and character consistency.
- Automate Performance Benchmarking: Build automated benchmarking systems to rigorously evaluate generative model performance across diverse cloud environments.
- Develop Ethical AI Pipelines: Create specialized ML pipelines for hallucination detection, bias measurement, and factual accuracy assessment, ensuring responsible AI.
- Craft Domain‑Specific Evaluation: Develop tailored evaluation frameworks for specific use cases, focusing on content appropriateness, brand alignment, and safety compliance.
- Integrate Human-in-the-Loop: Implement human‑in‑the‑loop evaluation systems, collaborating with domain experts to refine and validate AI outputs.
- Advance AI Techniques: Implement cutting‑edge generative AI techniques, including diffusion models, transformer variants, and mixture of experts architectures.
- Champion AI Safety: Develop constitutional AI and AI safety techniques to ensure responsible content generation.
- Strengthen Model Robustness: Build adversarial training systems to significantly improve model resilience and performance.
- Optimize Prompt Engineering: Research and implement advanced prompt engineering and in‑context learning optimization strategies.
- Design Novel Architectures: Create innovative architectures tailored for specific generative tasks, pushing the boundaries of what’s possible.
- Optimize for Production: Design A/B testing frameworks for continuous generative model comparison and optimization.
- Achieve Real‑Time Inference: Build real‑time inference optimization solutions for low‑latency content generation.
- Scale Model Serving: Implement robust model serving infrastructure with auto‑scaling and load‑balancing capabilities.
- Ensure Continuous Performance: Create comprehensive model monitoring, drift detection, and automatic retraining systems.
- Enhance AI Performance: Develop caching and retrieval systems to significantly improve generative AI performance and efficiency.
- Generative AI & Deep Learning:
- 5+ years of hands‑on machine learning engineering experience, with at least 2 years specifically focused on generative AI.
- Strong experience with transformer architectures,…
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