Junior Machine Learning / AI Engineer (Entry-Level)

About the Role

We are looking for a motivated Junior Machine Learning / AI Engineer to join our AI/ML team. This is an entry-level opportunity for candidates interested in building and deploying Machine Learning, Generative AI, and data-driven applications. You will work with experienced engineers and gain hands-on exposure to real-world Machine Learning, Deep Learning, Generative AI, and MLOps projects.

Who Should Apply

This role is intended for candidates with 0–1 year of full-time professional ML/AI experience. No prior full-time professional experience is required. Academic projects, internships, bootcamp projects, GitHub projects, and personal AI/ML projects are highly valued. Recent graduates and candidates transitioning into Machine Learning/AI are encouraged to apply.

Key Responsibilities

• Develop, train, test, and evaluate Machine Learning and Deep Learning models.
• Perform data preprocessing, feature engineering, model evaluation, and optimization.
• Build AI applications using LLMs, Generative AI, RAG, embeddings, and vector databases.
• Work with Python, Pandas, NumPy, Scikit-learn, TensorFlow and/or PyTorch.
• Assist with deploying ML/AI models and APIs to production environments.
• Work with cloud platforms such as AWS, Azure, or GCP.
• Collaborate with Data Scientists, ML Engineers, Data Engineers, and Software Engineers.
• Use Git/GitHub for version control and collaborative development.

Required Skills & Qualifications

Education

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, or a related field.
• Equivalent practical training or relevant project experience may also be considered.

Experience

• 0–1 year of professional ML/AI experience.

Technical Skills

• Strong foundational knowledge of Python and SQL.
• Understanding of Machine Learning algorithms, statistics, data preprocessing, and model evaluation.
• Familiarity with Scikit-learn, TensorFlow, or PyTorch.
• Exposure to Generative AI, LLMs, prompt engineering, RAG, LangChain/LlamaIndex, or vector databases is a plus.
• Basic understanding of REST APIs, Git/GitHub, Docker, and cloud platforms is preferred.
• Familiarity with MLOps, MLflow, CI/CD, or model monitoring is a plus.

Soft Skills

• Strong analytical and problem-solving skills.
• Good communication and collaboration abilities.
• Ability and willingness to learn new AI/ML technologies.
• Strong interest in building practical, production-oriented AI solutions.