Junior AI/ML Engineer

Role Overview

We are looking for a motivated Junior AI/ML Engineer with 1+ years of hands-on experience in developing, deploying, and maintaining machine learning solutions. The ideal candidate should have a strong foundation in machine learning concepts, data processing, and software development, with a passion for solving real-world problems using AI technologies.

Responsibilities

• Develop, train, evaluate, and optimize machine learning models for business applications.
• Collaborate with data scientists, software engineers, and product teams to deliver AI-driven solutions.
• Perform data collection, preprocessing, feature engineering, and exploratory data analysis.
• Implement and maintain ML pipelines for model training, validation, and deployment.
• Deploy machine learning models into production environments and monitor their performance.
• Work with large datasets and databases to extract insights and support model development.
• Research and experiment with new AI/ML techniques, tools, and frameworks.
• Document models, processes, and technical solutions for knowledge sharing and compliance.
• Troubleshoot and improve existing AI/ML systems for scalability and efficiency.

Requirements

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, or a related field.
• 1+ years of professional experience in Machine Learning, Artificial Intelligence, or Data Science.
• Strong programming skills in Python.
• Experience with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, or Keras.
• Knowledge of data manipulation and analysis using Pandas, NumPy, and SQL.
• Understanding of supervised and unsupervised learning algorithms.
• Familiarity with model evaluation techniques and performance metrics.
• Experience with version control systems such as Git.
• Basic understanding of cloud platforms (AWS, Azure, or GCP) and MLOps concepts.
• Strong analytical, problem-solving, and communication skills.

Nice to Have

• Experience working with Generative AI, Large Language Models (LLMs), or Natural Language Processing (NLP).
• Familiarity with frameworks such as LangChain, LlamaIndex, or similar AI orchestration tools.
• Exposure to containerization technologies such as Docker and orchestration tools like Kubernetes.
• Knowledge of CI/CD pipelines and model deployment practices.
• Experience with vector databases and retrieval-augmented generation (RAG) systems.
• Understanding of prompt engineering and AI model fine-tuning techniques.

Skills

• Python
• PyTorch
• TensorFlow
• AWS
• Docker

Benefits

• Flexible schedule
• Health insurance
• Leave encashment
• Provident Fund