To Apply for this Job Click Here
Machine Learning Engineer (GenAI Focus)
Role Overview
Seeking a senior-level Machine Learning Engineer to design and build Generative AI and LLM-based solutions in a modern, cloud-native environment. This role focuses on rapid prototyping, experimentation, and production-ready implementations that accelerate AI adoption across the organization.
Must-Have Qualifications
- 6+ years of experience in software engineering, ML engineering, or AI engineering
- 2+ years of hands-on experience with AI/ML initiatives involving GenAI, LLMs, automation, or advanced data platforms
- Strong hands-on experience building and prototyping GenAI solutions such as chatbots, summarization systems, copilots, or automation workflows
- Practical experience with LLM techniques including:
- Prompt engineering
- Retrieval-Augmented Generation (RAG) pipelines
- Embeddings and vector search
- LLM evaluation and fine-tuning
- Proficiency with modern ML frameworks and libraries (e.g., PyTorch, TensorFlow, Hugging Face, LangChain)
- Experience deploying ML/AI solutions in cloud environments (AWS, Azure, or GCP)
- Experience building ML systems using relational, NoSQL, and/or vector databases
- Working knowledge of MLOps practices and tools such as MLflow, Docker, and Kubernetes
- Ability to design experiments, evaluate models, and benchmark performance
- Strong collaboration skills with product, data, and engineering partners
- Excellent communication skills with the ability to document, demo, and share knowledge effectively
- Ability to manage multiple initiatives simultaneously with strong attention to detail
Nice to Have
- Experience working in R&D, innovation, or fast-paced prototyping environments
- Background building internal platforms or reusable components that enable enterprise AI adoption
- Contributions to open source projects, patents, or technical publications in ML or GenAI
Interested candidates may submit their resumes online or call at 310-906-4780 for further information regarding the position.
