AI/ML Engineer (Remote)
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Key skills for this role
About the Role
We are seeking an AI/ML Engineer to work on a contractor basis, contributing to the development of next-generation AI systems. You will design and deploy machine learning models, collaborate with cross-functional teams, and optimize data pipelines.
Key Skills for This Role
Responsibilities
- Design, develop, and deploy machine learning models to address complex business and technical challenges in alignment with AI system requirements
- Collaborate with cross functional teams to translate domain specific expertise into structured training data, evaluations, and feedback loops that enhance AI model performance
- Implement, optimize, and maintain ETL processes to ensure efficient data ingestion, transformation, and management for AI model training
- Utilize Python and relevant libraries to create clean, efficient, and reusable code for machine learning applications and data pipelines
- Continuously monitor, evaluate, and improve the accuracy and performance of deployed AI models through rigorous testing and iterative refinement
Requirements
- Proficiency in Python and familiarity with machine learning libraries such as scikit learn, TensorFlow, or PyTorch, with experience in model development and deployment
- Strong understanding of ETL processes, data pipelines, and tools for data ingestion, transformation, and management in AI applications
- Experience in developing and optimizing machine learning models, including feature engineering, model training, and evaluation
- Ability to collaborate effectively with technical and non technical stakeholders to translate domain knowledge into actionable AI inputs
- Familiarity with data quality assessment, performance monitoring, and iterative improvement of AI models in production environments
Full Job Posting
Role Overview
- We are hiring for one of our clients, seeking an AI/ML Engineer to work on a contractor basis.
- In this role, you will contribute to the development of next generation AI systems by leveraging domain expertise to shape how models learn, reason, and perform through high quality, real world input.
- Your work will directly impact the performance and reliability of AI models used by leading organizations globally.
Key Responsibilities
- Design, develop, and deploy machine learning models to address complex business and technical challenges in alignment with AI system requirements.
- Collaborate with cross functional teams to translate domain specific expertise into structured training data, evaluations, and feedback loops that enhance AI model performance.
- Implement, optimize, and maintain ETL processes to ensure efficient data ingestion, transformation, and management for AI model training.
- Utilize Python and relevant libraries to create clean, efficient, and reusable code for machine learning applications and data pipelines.
- Continuously monitor, evaluate, and improve the accuracy and performance of deployed AI models through rigorous testing and iterative refinement.
Required Skills & Qualifications
- Proficiency in Python and familiarity with machine learning libraries such as scikit learn, TensorFlow, or PyTorch, with experience in model development and deployment.
- Strong understanding of ETL processes, data pipelines, and tools for data ingestion, transformation, and management in AI applications.
- Experience in developing and optimizing machine learning models, including feature engineering, model training, and evaluation.
- Ability to collaborate effectively with technical and non technical stakeholders to translate domain knowledge into actionable AI inputs.
- Familiarity with data quality assessment, performance monitoring, and iterative improvement of AI models in production environments.
More About the Opportunity
- This role offers a distinctive opportunity to work within a global network of experts contributing to the human intelligence layer for AI.
- You will engage with cutting edge reinforcement learning environments and advanced evaluation frameworks, enabling you to directly influence how AI systems evolve.
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