Job Title: Gen AI Developer
Location: Bellevue, WA / Seattle, WA / Everett, WA / Renton, WA / Richardson, TX / Plano, TX / Dallas, TX
Full Time
Job Description
Must Have Technical/Functional Skills
Experience:
• Experience in machine learning, data science, or related fields.
• Hands-on experience with generative models (e.g., GANs, VAEs, diffusion models) and LLMs.
• Experience with ML frameworks (e.g., TensorFlow, PyTorch, JAX).
• Familiarity with cloud environments (AWS Sagemaker, Azure ML, or GCP AI Platform).
• Strong programming skills in Python (preferred) or similar languages.
• Proficiency in using libraries like Hugging Face, LangChain, or NVIDIA BioNeMo.
• Knowledge of Docker, Kubernetes, and CI/CD pipelines for deployment.
• Understanding of NLP, computer vision, or multimodal AI techniques.
• Strong problem-solving skills and a passion for AI-driven innovation.
• Experience with Retrieval-Augmented Generation (RAG) techniques and vector databases (e.g., Pinecone, Weaviate, Milvus).
Responsibilities
Model Development and Deployment:
• Design, fine-tune, and deploy generative AI models (e.g., Llama, GPT, Stable Diffusion) for various applications.
• Train and optimize large language models (LLMs) for tasks such as natural language understanding, summarization, and conversational AI.
2. Data Pipeline Management:
• Develop and maintain robust data pipelines for model training and inference.
• Clean, preprocess, and manage large-scale datasets to support AI projects.
3. Integration and Scalability:
• Implement ML models in production environments using tools like TensorFlow, PyTorch, or Hugging Face.
• Optimize models for performance, scalability, and cost-efficiency on cloud platforms (AWS, Azure, GCP).
4. Collaboration and Innovation:
• Work with product managers, data engineers, and software developers to align AI solutions with business objectives.
• Stay updated with the latest research and advancements in Gen AI and ML.
5. System Monitoring and Maintenance:
• Monitor deployed models for performance and accuracy; implement retraining and versioning strategies.
• Ensure systems meet ethical, privacy, and compliance standards