AI Developer

Job Title: AI Developer / Junior Artificial Intelligence Developer

Department: Artificial Intelligence / Machine Learning / Software Development

Experience: 0–1 Year (Freshers Can Apply)

Employment Type: Full-Time

Job Location: Bangalore, Karnataka

Qualification: B.E. / B.Tech / BCA / MCA / M.Sc. / B.Sc. (Computer Science / AI / Data Science / IT)

Job Summary

We are looking for an enthusiastic, technically skilled, and motivated AI Developer (Fresher) to join our Artificial Intelligence and Machine Learning development team in Bangalore.

The selected candidate will assist in designing, developing, testing, and integrating AI-powered applications and machine learning models. The role involves working with Python, data preprocessing, machine learning algorithms, AI APIs, and modern artificial intelligence frameworks.

The ideal candidate should possess strong programming fundamentals, analytical thinking, problem-solving abilities, and a basic understanding of artificial intelligence, machine learning, and generative AI technologies.

Key Responsibilities

1. AI & Machine Learning Development

• Assist in developing and implementing AI and machine learning solutions.
• Build and test basic machine learning models for classification, regression, and prediction tasks.
• Support model training, evaluation, and performance improvement.
• Work with structured and unstructured datasets.
• Collaborate with senior AI engineers and data scientists on development projects.
• Document model development activities and technical findings.

2. Python Programming & Application Development

• Write clean, efficient, and reusable Python code.
• Develop scripts for data processing, automation, and AI-related tasks.
• Assist in integrating AI models into software applications.
• Debug and troubleshoot Python applications.
• Follow coding standards and software development best practices.

3. Data Collection & Preprocessing

• Assist in collecting, cleaning, and preparing datasets.
• Handle missing values, duplicates, and inconsistent data.
• Perform basic exploratory data analysis.
• Use Python libraries for data manipulation and visualization.
• Support feature engineering and dataset preparation.
• Maintain data quality and accuracy.

4. Generative AI & Large Language Models

• Assist in developing applications using generative AI models and APIs.
• Work with large language models (LLMs) for text generation, summarization, classification, and information extraction.
• Develop and test prompts for AI-powered applications.
• Support the integration of AI services into web or backend applications.
• Gain exposure to retrieval-augmented generation (RAG) and vector databases.
• Evaluate AI-generated outputs for accuracy, relevance, and reliability.

5. AI Model Testing & Optimization

• Perform basic testing and validation of AI models.
• Evaluate model performance using appropriate metrics.
• Identify errors, inconsistencies, and potential bias in model outputs.
• Assist in improving model accuracy and efficiency.
• Support debugging and troubleshooting of AI applications.
• Document testing results and performance observations.

6. API Integration & Deployment

• Assist in integrating machine learning models with REST APIs.
• Support backend AI application development using Flask or FastAPI.
• Gain exposure to model deployment and cloud environments.
• Assist in maintaining AI application functionality.
• Follow security, privacy, and responsible AI development practices.

7. Research & Team Collaboration

• Research emerging AI technologies, frameworks, and development tools.
• Participate in technical discussions, code reviews, and project meetings.
• Collaborate with software developers, data engineers, and AI specialists.
• Maintain technical documentation and development reports.
• Continuously improve knowledge of machine learning and generative AI.

Required Technical Skills

1. Programming Languages

• Good understanding of Python programming.
• Knowledge of variables, functions, loops, classes, and objects.
• Understanding of object-oriented programming concepts.
• Familiarity with data structures and algorithms.
• Basic knowledge of SQL.

2. Machine Learning Fundamentals

• Understanding of supervised and unsupervised learning.
• Knowledge of classification, regression, and clustering.
• Familiarity with model training and testing.
• Basic understanding of overfitting, underfitting, and cross-validation.
• Awareness of common machine learning algorithms.

3. Python Libraries

• NumPy for numerical computing.
• Pandas for data manipulation.
• Matplotlib or Seaborn for data visualization.
• Scikit-learn for machine learning.
• Basic familiarity with TensorFlow or PyTorch will be an advantage.

4. Generative AI & LLM Fundamentals

• Basic understanding of generative AI and large language models.
• Familiarity with prompt engineering concepts.
• Awareness of AI APIs and model integration.
• Basic understanding of embeddings and vector databases.
• Familiarity with LangChain, LlamaIndex, or Hugging Face will be an advantage.
• Awareness of retrieval-augmented generation (RAG).

5. Mathematics & Statistics

• Basic understanding of linear algebra.
• Knowledge of probability and statistics.
• Familiarity with descriptive statistics.
• Understanding of model evaluation metrics.
• Basic knowledge of optimization concepts.

6. Database & API Knowledge

• Basic understanding of SQL databases.
• Familiarity with MySQL or PostgreSQL.
• Knowledge of REST APIs and JSON.
• Basic understanding of Flask or FastAPI.
• Awareness of data storage and retrieval concepts.

7. Development Tools

• Jupyter Notebook or Google Colab.
• Visual Studio Code or PyCharm.
• Git and GitHub.
• Basic familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Awareness of Docker and model deployment concepts will be an advantage.

Required Soft Skills

• Strong analytical and logical reasoning abilities.
• Good problem-solving and debugging skills.
• Curiosity and interest in artificial intelligence.
• Attention to detail and data accuracy.
• Effective verbal and written communication.
• Ability to work collaboratively in technical teams.
• Good time-management and organizational skills.
• Adaptability to new technologies and frameworks.
• Research-oriented thinking.
• Willingness to learn and experiment with AI technologies.

Educational Qualifications

• B.E. / B.Tech in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Information Technology, or related disciplines.
• BCA / MCA / B.Sc. / M.Sc. in Computer Science, Data Science, or related fields.
• Fresh graduates from the 2025 and 2026 batches are encouraged to apply.
• Candidates with relevant AI certifications, internships, or academic projects will have an added advantage.

Preferred Qualifications

• Academic or personal projects involving machine learning or AI applications.
• Practical knowledge of Python and Scikit-learn.
• Familiarity with TensorFlow or PyTorch.
• Experience working with datasets and performing exploratory data analysis.
• Basic exposure to generative AI APIs.
• Understanding of prompt engineering and LLM applications.
• Familiarity with Hugging Face, LangChain, or vector databases.
• Basic experience developing APIs using Flask or FastAPI.
• Knowledge of Git and version control.
• GitHub portfolio demonstrating AI or machine learning projects.
• Awareness of responsible AI, data privacy, and model evaluation.

Key Performance Indicators (KPIs)

• Quality and functionality of developed AI applications.
• Accuracy and reliability of machine learning models.
• Timely completion of assigned development tasks.
• Code readability, maintainability, and documentation quality.
• Accuracy of data preprocessing and validation.
• Effectiveness of debugging and issue resolution.
• Successful integration of AI models and APIs.
• Adherence to data security and responsible AI practices.
• Collaboration with AI and software development teams.
• Continuous improvement in technical knowledge and development skills.

Ideal Candidate

We are seeking a passionate, self-motivated, and technically curious fresher who wants to build a career in Artificial Intelligence and Machine Learning.

The candidate should demonstrate good Python programming knowledge, strong analytical thinking, a basic understanding of machine learning algorithms, and an interest in generative AI applications.

Practical exposure through academic projects, internships, Kaggle notebooks, GitHub repositories, or AI-based applications will be considered an advantage.

A willingness to learn emerging AI technologies, experiment with new frameworks, and contribute to developing reliable, scalable, and responsible AI solutions is essential.