Responsibilities
- Build and fine-tune generative models for text-to-image, text-to-video, image-to-text, and audio-based applications
- Develop and deploy ML pipelines for training, inference, and evaluation
- Design custom evaluation frameworks to assess model quality, safety, and accuracy
- Implement real-time and batch inference systems with performance and scalability in mind
- Collaborate with engineering and platform teams to productionize ML solutions
- ML Frameworks: PyTorch, TensorFlow, Hugging Face
- Models: Diffusion models, large language models, multi-modal models
- Training: Distributed training, fine-tuning techniques (LoRA, QLoRA)
- Cloud & Infra: AWS, Azure, or GCP; Docker, Kubernetes
- Data & MLOps: Vector databases, model monitoring, A/B testing frameworks
Basic qualifications
- 3+ years of experience in machine learning or computer vision roles
- Hands-on experience building and deploying generative AI models
- Strong Python skills and experience with modern ML frameworks
- Experience deploying models in cloud-based, containerized environments
Preferred qualifications
- Experience with multi-modal or real-time ML systems
- Familiarity with model evaluation, safety, or responsible AI practices
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Ai Machine Learning Computer Vision Pytorch Tensorflow Generative Ai