
Advanced AI/ML Engineer for Cutting-Edge GenAI Projects
1 week ago
Job Title
We are seeking a highly skilled AI/ML Engineer to leverage cutting-edge Generative AI technologies and drive innovation in software development and business processes.
- Develop and deploy applications using Generative AI frameworks and technologies such as Prompt Engineering, Fine Tuning, Few-Shot learning, Retrieval-Augmented Generation (RAG), Text-to-Text Transfer Transformation (T5) Framework, and data embedding techniques.
- Design and implement chunking strategies for diverse datasets, leveraging experience with vector databases like Pinecone, Weaviate, or Milvus.
- Collaborate with cross-functional teams to design, implement, and optimize AI-driven solutions, with exposure to cloud-native AI platforms considered a plus.
- Implement RAG frameworks to enhance information retrieval and response accuracy.
- Stay updated on emerging trends and technologies in the GenAI and AI/ML landscape.
Required Skills and Qualifications:
- Proficiency in Generative AI frameworks and technologies, including Prompt Engineering, Fine Tuning, Few-Shot learning, Retrieval-Augmented Generation (RAG), Text-to-Text Transfer Transformation (T5) Framework, and data embedding techniques.
- Expertise in designing and implementing chunking strategies for diverse datasets, leveraging experience with vector databases like Pinecone, Weaviate, or Milvus.
- Solid programming skills in Python, with experience in AI/ML libraries such as TensorFlow, PyTorch, or Hugging Face Transformers.
- Familiarity with cloud platforms and services for AI/ML workloads.
- Experience with API integration for AI services and building scalable applications.
Benefits:
- Opportunity to work on cutting-edge GenAI projects and technologies.
- Chance to collaborate with cross-functional teams and contribute to innovative solutions.
- Professional growth and development opportunities in the field of AI/ML.
What You Should Expect in This Role:
- Develop and deploy applications using Generative AI frameworks and technologies.
- Implement RAG frameworks to enhance information retrieval and response accuracy.
- Design and implement chunking strategies for diverse datasets.
- Build and manage data embeddings using various vector databases.
- Collaborate with data engineers and scientists to integrate AI solutions seamlessly into existing pipelines.
- Explore and implement best practices for leveraging Amazon Bedrock and Azure OpenAI services.
- Stay updated on emerging trends and technologies in the GenAI and AI/ML landscape.
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