AI/ML Data Engineer

A full-time contract ML/AI Data Engineer with a strong background in deep learning and natural language processing is required to support the development of proprietary models of meaning for private corporations and investment firms. The role involves designing, building, and optimizing scalable machine learning pipelines, with a particular focus on large language models (LLMs) and data engineering best practices. Working remotely, the successful candidate will collaborate with a team that includes pioneering expertise in natural language processing, contributing to innovative solutions that advance language understanding and applied AI. This is an excellent opportunity for a motivated professional to gain exposure to cutting-edge NLP research while applying practical skills to real-world data challenges.

Deliverables

• Design and implement robust ML/AI data pipelines to support ongoing model development and deployment.
• Train, fine-tune, and evaluate large language models for specialized use cases.
• Apply deep learning techniques to NLP tasks such as semantic analysis, text classification, and information extraction.
• Optimize data workflows for performance and scalability using platforms such as Snowflake.
• Collaborate with cross-functional team members to translate research into production-ready solutions.
• Document processes, maintain code repositories, and ensure reproducibility of experiments and models.
• Provide insights and recommendations to enhance the efficiency and accuracy of proprietary NLP models.

Requirements

• Strong academic or professional background in data science, machine learning, or AI engineering.
• Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch.
• Expertise in natural language processing, with familiarity in techniques such as embeddings, transformers, and semantic modeling.
• Experience working with large language models, including training, fine-tuning, and evaluation.
• Proficiency in Python and common ML/NLP libraries (Hugging Face Transformers, spaCy, scikit-learn, etc.).
• Knowledge of Snowflake or other cloud-based data platforms for managing and optimizing data pipelines.
• Strong problem-solving skills and ability to work independently in a remote environment.
• Excellent communication skills for collaborating with both technical and non-technical stakeholders.
• Commitment to delivering high-quality, reproducible, and scalable solutions.

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