About this opportunity
247Hire lists this Machine Learning Engineer opportunity in orlando, Florida. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Seeking a Machine Learning Engineer for the following role - Generative AI & ML Frameworks: PyTorch, TensorFlow, Hugging Face Transformers, Diffusers Training: DeepSpeed, Accelerate, Ray, distributed training frameworks Models: GPT/LLaMA variants, DALL‑E/Stable Diffusion, Whisper, multi‑modal models Fine‑tuning: LoRA, QLoRA, DreamBooth, custom training pipelines Infrastructure & Platforms Cloud: GCP Vertex AI, Azure OpenAI, AWS Bedrock, multi‑cloud orchestration Serving: TensorRT, ONNX, TorchServe, custom inference servers Orchestration: Kubernetes, Docker, APIGEE, Terraform Data: Vector databases (Pinecone, Weaviate), feature stores, data versioning Specialized Tools Frameworks: Autogen, LangChain, MCP (Model Context Protocol) Evaluation: Custom metrics, human evaluation platforms, A/B testing frameworks Monitoring: MLflow, Weights & Biases, custom dashboards
Responsibilities
Build text‑to‑image and text‑to‑video generation systems
Develop speech synthesis and voice cloning models with safety guardrails for character voices
Create image‑to‑text and video‑to‑text systems for content analysis and accessibility
Implement cross‑modal generation (text + image? video, audio + text? multimedia content)
Build real‑time generative systems for interactive experiences (IoT)
Model Evaluation & Quality Assurance
Design and implement custom evaluation models for content assessment (brand safety, content ratings, character consistency)
Build automated benchmarking systems for generative model performance across multi‑cloud environments
Develop specialized ML pipelines for hallucination detection, bias measurement, and factual accuracy assessment
Create domain‑specific evaluation frameworks for use cases (content appropriateness, brand alignment, safety compliance)
Implement human‑in‑the‑loop evaluation systems with domain experts
Research & Advanced Techniques: Implement cutting‑edge generative AI techniques: diffusion models, transformer variants, mixture of experts
Develop constitutional AI and AI safety techniques for responsible content generation
Build adversarial training systems to improve model robustness
Research and implement prompt engineering and in‑context learning optimization
Create novel architectures for specific generative tasks
Production AI/ML Systems: Design A/B testing frameworks for generative model comparison and optimization
Build real‑time inference optimization for low‑latency content generation
Implement model serving infrastructure with auto‑scaling and load balancing
Create model monitoring, drift detection, and automatic retraining systems
Develop caching and retrieval systems for improved generative AI performance
Key Projects & Use Cases (Marketing Content Generation)
Build text‑to‑video systems for promotional content creation
Develop brand‑consistent image generation with style transfer
Create voice synthesis for character‑based marketing campaigns
Theme Park Innovation
Implement real‑time generative systems for interactive guest experiences
Build personalized content generation based on guest preferences
Develop safety‑aware content generation for operational communications
Customer Experience Enhancement
Create personalized response generation for customer support
Build multi‑lingual content generation for global audiences
Develop accessibility‑focused content generation (audio descriptions, simplified language)
Basic Qualifications
5+ years of hands‑on machine learning engineering with 2+ years focused on generative AI
Strong experience with transformer architectures, diffusion models, and large language models
Proven track record with model fine‑tuning, RLHF, and parameter‑efficient training techniques
Experience with multi‑modal AI systems (text+vision, text+audio, cross‑modal generation)
Deep understanding of generative AI training dynamics, loss functions, and optimization techniques
Technical Expertise
Expert‑level Python programming with TensorFlow/PyTorch and distributed training frameworks
Experience with cloud ML platforms (GCP Vertex AI, Azure OpenAI, AWS Bedrock) and model serving
Strong background in computer vision, NLP, and audio processing for generative applications
Knowledge of MLOps, model versioning, and production deployment strategies
Experience with vector databases, embeddings, and retrieval‑augmented generation (RAG)
AI Safety & Evaluation
Experience building evaluation frameworks for generative AI systems
Knowledge of AI safety techniques: bias detection, content filtering, adversarial robustness
Understanding of responsible AI frameworks and red‑team methodologies
Familiarity with AI governance, model interpretability, and compliance requirements
Preferred Qualifications
Advanced degree in Machine Learning, Computer Science, or related field
Experience with industry applications (content creation, media analysis, interactive systems)
Knowledge of edge AI optimization and real‑time inference systems
Background in reinforcement learning and human preference modeling
Experience with large‑scale distributed training (multi‑GPU, multi‑node)
Contributions to open‑source AI projects or published research in generative AI
Education
BE/BS in Machine Learning, Computer Science, or related field
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Worksite address
orlando, FL, 32885, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.