Junior AI/ML Engineer

Experience: 0-1 Year

Key Responsibilities:

• Understand and deliver AI/ML solutions using cloud-based services.
• Participate in client discussions to understand requirements and formulate business and ML problems, and assist team members in solution implementation.
• Build and deliver solutions for AI/ML problems while addressing key data science requirements.
• Work on projects involving extraction of specific text fields from PDFs and images using OCR, parsing, text detection, machine learning, document layout analysis, and Python.
• Participate in the complete project lifecycle, including data collection, data integration, data cleaning, data analysis, visualization, and feature engineering.
• Assist with AI/ML model training, parameter tuning, model evaluation, and deployment.
• Develop and maintain processes and tools for monitoring model performance.
• Take ownership of assigned tasks and proactively identify and communicate potential issues, risks, and impacts.
• Develop modular, reusable, scalable training and inference pipelines.
• Work closely with developers, technical leads, QA engineers, and architects to develop and deliver solutions.
• Deliver well-tested and scalable code for data pipelines, system integration, and model training.
• Collaboratively solve complex problems and develop algorithms and software modules.
• Assist in developing scalable backend systems and microservices to automate ML model training and deployment.
• Contribute to AI services across areas such as Decision Support, Computer Vision, Speech, Text, NLP, and NLU.

Required Skills & Qualifications:

• B.Tech/B.E. in Computer Science, IT, AI/ML, Data Science, or a related field.
• 0-1 year of experience in AI/ML, Data Science, or Python development. Freshers with relevant internship experience are welcome to apply.
• Strong foundation in Artificial Intelligence, Machine Learning, Python, SQL, and database technologies such as MySQL, PostgreSQL, Oracle, and MongoDB.
• Familiarity with at least one cloud platform such as AWS, Azure, GCP, or Snowflake.
• Good knowledge of Deep Learning, NLP, Computer Vision, OCR, and Generative AI.
• Good knowledge of TensorFlow/PyTorch, REST APIs, Docker, LLMs, and RAG.
• Relevant AI/ML, Data Science, Python, or Cloud certifications are an advantage.
• Strong problem-solving, analytical, communication, and teamwork skills.