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# ML Engineer / Data Scientist

- **Company:** Macpower Digital Assets Edge LLC
- **Location:** Cupertino, CA, United States
- **Experience:** Expert
- **Salary:** $141,440.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Big Data, Cloud Computing, Information Engineering, Data Transformation, Data Normalization, Django Web Framework, Information Retrieval, Python (Programming Language), Search Algorithms, Machine Learning, Natural Language Processing, NumPy, Tensorflow, Unstructured Data, Scripting, Feature Engineering, Pytorch, LangChain, Retrieval-Augmented Generation, Transfer Learning, Flask (Web Framework), Large Language Models, Multi-Agent Systems, Prompt Engineering, Llamaindex, AWS Lambda, Indexer, Agentic-AI, Fastapi, Pandas, Containerization, Pyspark, Scikit Learn, Information Technology, Cloudwatch, Api Gateway, Streamlit Framework, Docker, Data Generation
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/ml-engineer-data-scientist-cupertino-ca--1f498c60-c2ee-4d19-9eef-4046948d8da9

## About the Role

Data Science, Python Programming/Scripting Language, Artificial Intelligence (AI), Machine Learning, Amazon Web Services (AWS), Search Algorithms, Information Retrieval, Information Models, Natural Language Processing (NLP), Predictive Modeling, * Proven hands-on experience in Python programming, with expertise in popular AI/ML frameworks such as TensorFlow, PyTorch, scikit-learn, LangChain, and LlamaIndex.

 * Strong background in building and implementing machine learning models.
 * Hands-on experience in developing AI/ML/GenAI solutions using AWS services such as SageMaker.
 * Experience with search algorithms, indexing techniques, summarization, and retrieval models for effective information retrieval tasks.
 * Practical experience with RAG (Retrieval-Augmented Generation) architecture and its applications in Natural Language Processing (NLP).
 * Good exposure to Agentic / Multi-agent frameworks.
 * End-to-end experience in developing machine learning and deep learning solutions, including predictive modeling, applied machine learning, and natural language processing.
 * Expertise in data engineering, including preprocessing and cleaning large datasets using Python, PySpark, and tools like Pandas and NumPy. Proficient in techniques such as data normalization, feature engineering, and synthetic data generation.
 * Solid understanding of cloud computing principles and experience in deploying, scaling, and monitoring AI/ML/GenAI solutions on platforms like AWS.
 * Proficient in deploying and monitoring ML solutions using AWS Lambda, API Gateway, and ECS, and tracking performance using CloudWatch.
 * Experience with Docker and containerization technologies.
 * Strong communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders, and to collaborate effectively with cross-functional teams., * A Master's degree in Computer Science or Engineering.
 * Minimum of 14 years of IT experience.
 * At least 7 years of experience as a Machine Learning Engineer or Data Scientist.
 * Hands-on experience using Python and APIs such as Flask, Django, or FastAPI.
 * Practical experience with tools such as LangChain, LlamaIndex, and Streamlit.
 * Experience working with semi-structured and unstructured data.
 * Must have implemented at least one use case using Large Language Models (LLMs).
 * Must have experience in prompt engineering and fine-tuning LLMs using techniques like LoRA or PEFT.
 * Must have implemented a use case using RAG architecture.
 * Experience with a Multi-agent framework is a strong plus.