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We are looking for an AI ML Engineer - Location: Remote - Position Type 6-12+ Months Contract Position.
Job Title: AI ML Engineer
Employment Type: Contract duration 6 to 12months
Work location: Remote in USA (may require travelling to client office based on business need)
About the role:
Client is looking for an AI Engineer who will be responsible for designing, developing, and deploying machine learning models in production environments. This role will involve working with large datasets, building and evaluating models, and integrating them with other systems. The ideal candidate will have a strong understanding of machine learning algorithms, experience with model deployment and monitoring, and a passion for staying at the forefront of AI technology.
Job Responsibilities:
- Model Development: Design, develop, and implement machine learning models to address business challenges.
- Model Evaluation and Optimization: Evaluate model performance, fine-tune parameters, and optimize models for accuracy and efficiency.
- Production Deployment: Deploy models into production environments, ensuring scalability, reliability, and maintainability.
- Text2SQL AI Orchestration: Develop and implement solutions for natural language processing (NLP) tasks, including text-to-SQL conversion.
- VectorDB and LLM Integrations: Integrate vector databases and large language models (LLMs) into AI solutions. Embedding/Chunking Strategies: Develop and implement strategies for embedding and chunking data for efficient processing.
- Prompt Engineering: Design and refine prompts for LLMs to optimize performance.
- Platform Expertise: Utilize platforms like Bedrock and Sagemaker for building and deploying AI solutions.
- Collaboration: Work closely with data scientists, engineers, and business stakeholders to deliver impactful AI solutions.
Mandatory Qualifications:
- 10+ years of experience in machine learning engineering or a related field.
- Strong understanding of machine learning algorithms and principles.
- Experience with model evaluation metrics, feedback loops, and optimization techniques.
- Proficiency in Python and relevant ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience with deploying and monitoring models in production environments.
- Knowledge of Text2SQL AI orchestration, vector databases, and LLM integration.
- Familiarity with embedding/chunking strategies and prompt engineering techniques.
- Experience with cloud platforms AWS (Bedrock, Sagemaker) and/or Azure/Google Cloud Platform.
- Strong problem-solving and analytical skills. Excellent communication and collaboration skills.
Additional / Nice-to-have Qualifications:
- Experience with MLOps practices and tools. Contributions to open-source ML projects or publications in relevant conferences.
- Certifications in AWS and/or other cloud platforms.