Tech Stack
AWSCloudPythonPyTorchScikit-LearnTensorflow
About the role
- Lead the fine-tuning and customization of OCR, Image-to-Text, and generative AI models tailored to client needs.
- Develop effective prompt engineering strategies to optimize generative AI outputs.
- Oversee data annotation and tagging workflows to maintain high-quality training data.
- Implement and maintain ML/AI model monitoring systems to ensure consistent performance post-deployment.
- Support MLOps activities including model versioning, deployment, and continuous integration.
- Collaborate cross-functionally to drive AI/ML solution integration and scalability.
- Leverage Python ML frameworks (TensorFlow, PyTorch, scikit-learn) and AWS AI/ML services (SageMaker, Lambda, S3).
- Mentor junior team members and foster a culture of innovation and continuous learning.
Requirements
- 8-10 years of experience in AI/ML development, with strong focus on OCR, Image-to-Text, and prompt engineering.
- Domain Experience in F&A is highly preferred.
- Proficient in Python and ML frameworks with practical experience in model fine-tuning.
- Deep understanding of data annotation, tagging, and dataset management.
- Basic knowledge of MLOps pipelines and deployment workflows.
- Experience with ML/AI model monitoring and troubleshooting in production environments.
- Hands-on experience with AWS AI/ML tools and cloud infrastructure.
- Excellent analytical, problem-solving, and communication skills.
- Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
OCRImage-to-Textgenerative AIprompt engineeringdata annotationmodel fine-tuningMLOpsmodel monitoringPythondataset management
Soft skills
analytical skillsproblem-solvingcommunicationmentoringcollaborationinnovationcontinuous learning
Certifications
Bachelor’s degree in Computer ScienceMaster’s degree in Data Science