▷ Apply in 3 Minutes! AI / ML Engineer

Job Title : AI / ML Engineer

Location : Hyderabad, India

Work Mode : Onsite (5 days / week)

Experience : 0–3 Years

Employment Type : Full-time

Position Overview :

We are looking for an enthusiastic and motivated AI / ML Engineer with 0–3 years of experience to join our team in Hyderabad. This is a full-time, onsite role where you will gain hands-on experience in building and deploying AI / ML applications. The ideal candidate should have a strong foundation in programming, machine learning concepts, and a passion for solving real-world problems using data and AI.

Key Responsibilities :

Assist in designing, building, and testing AI / ML models for real-world applications.

Work on data preparation, cleaning, preprocessing, and feature engineering.

Train and evaluate machine learning and deep learning models.

Collaborate with product and engineering teams to support AI / ML use cases.

Create basic dashboards, visualizations, and reports for stakeholders.

Stay updated on AI / ML frameworks, libraries, and tools to improve skills continuously.

Required Qualifications :

Bachelor’s degree in Computer Science, Data Science, AI / ML, or related field.

Internship or academic project experience in AI / ML is preferred.

Strong programming skills in Python.

Familiarity with ML frameworks / libraries : Scikit-learn, TensorFlow, or PyTorch.

Understanding of fundamental ML algorithms (classification, regression, clustering).

Basic experience with data handling using Pandas, NumPy.

Knowledge of SQL for data querying.

Preferred Skills :

Exposure to data visualization tools (Matplotlib, Seaborn, or Power BI / Tableau).

Awareness of cloud platforms (AWS SageMaker, Azure ML, Google AI Platform).

Understanding of version control (Git, GitHub).

Basic knowledge of NLP or Computer Vision libraries (NLTK, Spacy, OpenCV).

Eagerness to learn MLOps practices and AI deployment workflows.

Work Arrangement :

Location : Hyderabad (onsite only)

Work Schedule : Monday to Friday (5 days a week, in-office)