Senior Data Scientist
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Key skills for this role
About the Role
Presight seeks a Senior Data Scientist with at least 4 years of experience in Computer Vision and LLM-based systems. The role involves developing and deploying AI models for the oil & gas industry, including prototyping, end-to-end implementation, and monitoring.
Key Skills for This Role
Responsibilities
- Design, develop, and assess data driven algorithms for various tasks (regression, classification, segmentation, etc.) using cutting edge AI techniques
- Prototype and evaluate LLM based systems and multimodal models for tasks such as document understanding, knowledge extraction, and workflow automation
- Hands on implementation of AI models, from data preparation and cleaning to model deployment and maintenance in production
- Contribute to the solution design and collaborate with teams to integrate AI enabled software products for the oil & gas industry
- Evaluate and monitor AI solutions to ensure they align with project objectives, addressing data quality issues and continuously improving existing solutions
Requirements
- At least 4 years of experience demonstrating depth and breadth in Computer Vision projects (classification, detection, segmentation) with CV approaches
- Demonstrated experience with state of the art machine learning and/or deep learning technologies
- Demonstrated experience in developing, deploying and scaling end to end ML pipelines in industrial context
- Hands on experience building and deploying LLM applications (e.g., GPT, Llama, Falcon, Claude), including fine tuning, RAG systems, domain adaptation, or multimodal extensions
- Demonstrated experience designing and implementing agentic AI systems—task oriented agents, workflow orchestrators, tool using agents, or autonomous reasoning frameworks
- Strong foundation in applied mathematics and statistics
- Proficiency in machine learning and deep learning techniques
- Advanced Python programming skills for AI development
- Extensive experience with classic CV tools (OpenCV), deep learning frameworks (PyTorch, TensorFlow), and popular ML libraries (Scikit learn)
- Master’s degree or Ph.D. in Computer Science, Applied Mathematics, Statistics, or any AI related field
Full Job Posting
Overview
- Job Description Overview
Responsibilities
- Experimentation and Prototype Development: Design, develop, and assess data driven algorithms for various tasks (regression, classification, segmentation, etc.) using cutting edge AI techniques.
- Prototype and evaluate LLM based systems and multimodal models for tasks such as document understanding, knowledge extraction, and workflow automation.
- End to End Implementation: Hands on implementation of AI models, from data preparation and cleaning to model deployment and maintenance in production.
- Integration of Pipelines: Contribute to the solution design and collaborate with teams to integrate AI enabled software products for the oil & gas industry.
- Monitoring Model Performance: Evaluate and monitor AI solutions to ensure they align with project objectives, addressing data quality issues and continuously improving existing solutions.
Qualifications
- Requirements – Experience: At least 4 years of experience demonstrating depth and breadth in Computer Vision projects (classification, detection, segmentation) with CV approaches.
- Demonstrated experience with state of the art machine learning and/or deep learning technologies.
- Demonstrated experience in developing, deploying and scaling end to end ML pipelines in industrial context.
- Hands on experience building and deploying LLM applications (e.g., GPT, Llama, Falcon, Claude), including fine tuning, RAG systems, domain adaptation, or multimodal extensions.
- Demonstrated experience designing and implementing agentic AI systems—task oriented agents, workflow orchestrators, tool using agents, or autonomous reasoning frameworks.
- Experience in Geoscience applications to the Oil & Gas sector is a plus.
- Requirements – Key Skills: Strong foundation in applied mathematics and statistics.
- Proficiency in machine learning and deep learning techniques.
- Advanced Python programming skills for AI development.
- Extensive experience with classic CV tools (OpenCV), deep learning frameworks (PyTorch, TensorFlow), and popular ML libraries (Scikit learn).
- Comprehensive knowledge and practical application of diverse ML algorithms and DL architectures.
- Proficiency in essential development tools like PyCharm, Jupyter, ClearML, Git, and Docker.
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