AI/ML Engineer

ExamRoom.AI

ExamRoom.AI

Software Engineering, Data Science
Bengaluru, Karnataka, India
Posted on Thursday, May 9, 2024
Position Title: AI/ML Engineer (2-4 Years experience)
Reports To: VP of Data Science

Position Required Skills, Knowledge, and Abilities:

Programming and Data Handling: Proficient in programming languages such as Python or Java and capable of handling data of various forms and sizes.
Experience with Machine Learning Models: At least 2 years of experience in implementing machine learning models such as NLP, CNNs, RNNs, and basic familiarity with Transformer architectures.
Familiarity with Deep Learning Libraries: Strong practical knowledge of TensorFlow, PyTorch, or Keras.
Mathematical and Statistical Background: Good understanding of basic statistical concepts and their application in machine learning.
NLP Knowledge: Basic to moderate experience in working with NLP tasks and projects.
Image Processing Skills: Experience with basic tasks in computer vision such as image classification and object detection.
Understanding of ML Core Concepts: Knowledge of attention mechanisms, feature engineering, and basic transformers like BERT.
Technological Versatility: Comfortable working with various databases and familiar with APIs, JSON, and XML file formats.
Communication Skills: Able to effectively communicate technical details and project needs with team members and stakeholders.

Position Education and Experience (required and preferred):

Educational Background: Bachelor’s degree in computer science, Data Science, Artificial Intelligence, or related field.
Project Management: Some experience managing projects or components of projects in a technical setting.
Innovative Thinking: Ability to contribute ideas for new features and improvements based on the latest industry trends.

Position Responsibilities:

Develop and Implement ML Models: Build and refine machine learning models for NLP, image processing, and other applications.
Collaborate on Recommendation Systems: Assist in the development of recommendation systems that utilize both images and text.
Participate in Model Training: Help in setting up and managing the infrastructure for ML model training and deployment.
Support Data Analysis Tasks: Work on expression analysis projects using webcam input for emotion recognition.
Stakeholder Interaction: Communicate with business stakeholders to explain AI/ML capabilities, project progress, and realistic outcomes.
Continuous Learning: Keep abreast of the latest trends and research in AI/ML that can benefit ongoing projects.
Team Collaboration: Work effectively both as part of a team and independently, with guidance as needed to meet project goals.