Machine Learning Engineer

Machine Learning Engineer Work location Dearborn, MI Ideal to be local but not required. 12 month contract. NO H1s Resources will be in office 4 days a week. Teams Video interview 1 hour - 1 round $78.11 W2 +10 days PTO. REVIEW JD MAKE SURE REQUIRED SKILLS (highlighted red) ARE ON THE RESUME, IF NOT, DON'T SEND. Machine Learning Engineering Engineer 3 #1037421 Job Description:

• Employees in this role are responsible for designing, developing, and deploying cutting-edge Generative AI solutions, with a particular emphasis on Retrieval-Augmented Generation (RAG) systems.
• This involves leveraging various AI techniques, including vector databases and robust API development frameworks like FastAPI, and ensuring efficient deployment through containerization and MLOps practices, to build intelligent applications that enhance user experience and automate complex processes.

• GCP, Big Data, Artificial Intelligence & Expert Systems, API
• GCP - Mid Level
• Big Data - Entry level
• Artificial Intelligence & Expert Systems - Entry Level
• API : Mid-level

• Experience deploying AI/ML models into production environments at scale.
• Previous experience in a large enterprise or fast-paced technology environment.

• Strong understanding of Generative AI principles and architectures, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.
• Proven experience in building and deploying RAG systems, including the use of **Vector Databases**.
• Proficiency in Python programming.
• Solid experience with SQL for data manipulation and querying.
• Hands-on experience with Google Cloud Platform (GCP) services relevant to AI/ML.
• Basic understanding and practical experience with Machine Learning model fine-tuning.
• Familiarity with data engineering concepts and practices.
• Expertise in prompt engineering techniques for interacting with LLMs.
• Experience with the OpenAI SDK.
• Experience developing robust APIs, preferably with **FastAPI**.
• Proficiency with **version control systems (e.g., Git)**.
• Experience with **containerization technologies (e.g., Docker)**.

• Design, develop, and implement Generative AI models and applications, specifically focusing on building and optimizing RAG systems, including the integration and management of vector databases, using various technology stacks, with a preference for the OpenAI SDK.
• Apply fundamental Machine Learning concepts, including model fine-tuning, to improve the performance and accuracy of AI solutions, and deploy them via efficient APIs, such as those built with FastAPI, utilizing containerization for consistent environments.
• Perform data engineering tasks to prepare, process, and manage data pipelines essential for training, evaluating, and deploying Generative AI models, including data ingestion for vector databases, ensuring data quality and accessibility.
• Utilize advanced prompt engineering techniques to optimize interactions with large language models and achieve desired outputs, and expose these capabilities through well-designed APIs.
• Collaborate with cross-functional teams to integrate AI solutions into existing products and services, ensuring scalability, reliability, and maintainability on cloud platforms, particularly Google Cloud Platform (GCP), adhering to MLOps principles and continuous integration/continuous deployment (CI/CD) practices. 3B Staffing LLC