Machine Learning Engineer- 2 Job in Bangalore at Parspec

Parspec is hiring for the role of Machine Learning Engineer- 2!

Responsibilities of the Candidate:

• Design and develop Computer Vision, NLP, and Recommendation Systems for our applications.
• Research and implement novel deep learning architectures to solve complex data science problems.
• Develop, train, and deploy deep learning and machine learning models that are scalable and extensible.
• Collaborate with product managers, UX designers, and end-users to integrate software and AI components into fully functional systems.
• Participate in the complete product lifecycle—from concept design to development, integration, testing, and deployment.
• Build products that handle large data volumes efficiently while remaining highly scalable for onboarding new clients.
• Design complete end-to-end data pipelines and ML pipelines for seamless integration into production environments.
• Work closely with the leadership team on research and development efforts to explore cutting-edge technologies.
• Uphold our culture of engineering excellence by maintaining high standards in code quality and innovation.

Requirements:

• Bachelor’s or Master’s degree in Science or Engineering with strong programming, critical thinking, and analytical skills.
• Strong conceptual understanding of machine learning and deep learning principles.
• Expertise in Computer Vision or Natural Language Processing (NLP).
• Hands-on experience implementing ML projects in Python using libraries like NumPy, scikit-learn, matplotlib, pandas, etc.
• Proficiency in training deep learning models using TensorFlow/Keras or PyTorch.
• Ability to write clean, efficient, and bug-free code.
• Proven ability to lead initiatives from concept to operation while navigating challenges effectively.
• Experience working with applications hosted on AWS or Django web frameworks.
• Familiarity with databases and web application architecture.
• Experience working with OCR tools or PDF processing libraries.
• Strong knowledge of algorithms and data structures.
• Completed academic or online specializations in Machine Learning or Deep Learning.
• Participation in competitive programming (e.g., Kaggle competitions) or contributions to open-source projects.
• Experience working with geographically distributed teams across multiple time zones.