AI/ML Engineer
RemoteUnited States
Job Summary
Design, develop, and implement machine learning models and AI algorithms tailored to industry-specific use cases in predictive analytics, natural language processing, and computer vision. Collaborate with data engineers to build and maintain robust data pipelines, then optimize models for performance, scalability, and accuracy using techniques like hyperparameter tuning and feature engineering. Deploy these solutions into production environments using industry-standard tools while working closely with domain experts to integrate AI into upstream Oil & Gas processes for exploration, drilling, and production optimization. Monitor post-deployment performance to make iterative improvements and create comprehensive documentation for knowledge sharing.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field
- 3+ years of experience in AI/ML engineering
- Proven track record of developing and deploying machine learning models in a production environment
- Proficiency in programming languages such as Python, R, or Java
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Strong understanding of data structures, algorithms, and software design principles
- Experience with cloud platforms like AWS, Azure, or Google Cloud for deploying AI models
- Experience with containerization and orchestration tools like Docker and Kubernetes
- Strong problem-solving skills with the ability to analyze complex datasets and develop innovative AI solutions
- Excellent verbal and written communication skills
- Ability to collaborate effectively across multidisciplinary teams
Desired Qualifications
- Ph.D.
- Familiarity with big data technologies such as Hadoop, Spark, or Kafka
- Experience with natural language processing (NLP) and computer vision
- Experience with real-time data processing and streaming analytics
- Familiarity with ethical AI practices and the ability to implement AI models responsibly
- Experience in the Oil & Gas sector
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