onsite
AI/ML Engineer - Python/NLP
AI/ML Engineer - Python/NLP
The AI/ML Engineer will assist in developing and training AI/ML models, focusing on Python and NLP. Key responsibilities include data cleaning, validation, feature engineering, and supporting model testing and deployment. This role is for passionate fresh graduates or early-career professionals eager to build a career in AI & Machine Learning.
About the role
About the Role
RBHU Analytics is seeking a passionate fresh graduate or early-career professional to join as an AI/ML Engineer. This role is ideal for individuals aiming to build a career in Artificial Intelligence & Machine Learning, with a focus on Python and NLP. Candidates with academic projects, internships, or certifications in AI/ML will be preferred.
Education
- B.E. / B.Tech in Computer Science / IT / AI / ML / Data Science or related field
- Mathematics score ≥ 70% in both 10th and 12th standard (mandatory)
Key Skills & Knowledge
- Strong foundation in Artificial Intelligence & Machine Learning concepts
- Programming knowledge in Python (mandatory)
- Basic understanding of:
- Machine Learning algorithms (Regression, Classification, Clustering)
- Data preprocessing and data analysis
- Libraries such as NumPy, Pandas, Scikit-learn
- Exposure to Deep Learning / NLP / Computer Vision is an added advantage
- Familiarity with SQL, Git, Jupyter Notebook preferred
- Ability to understand problem statements and convert them into ML solutions
Soft Skills
- Good English communication skills (verbal & written)
- Strong analytical and logical thinking
- Willingness to learn and adapt to new technologies
- Ability to work independently as well as in a team
Eligibility Criteria (Mandatory)
- Resident of Mumbai
- BE / BTech graduate
- Maths ≥ 70% in 10th & 12th
- Good English language proficiency
Role & Responsibilities
- Assist in developing and training AI/ML models
- Work on data cleaning, validation, and feature engineering
- Support senior engineers in model testing and deployment
- Participate in research, experimentation, and documentation
- Continuously learn and apply new AI/ML techniques