Machine Learning Engineer

Data Scientist / ML Engineer

Experience: 0-1 years 

Location: Bangalore 

Job Type: Full Time 

About the Role

We are looking for an enthusiastic and eager-to-learn ML Engineer/Data Scientist to join our growing team. You'll work in a fast-paced, collaborative environment where you'll have the opportunity to learn from experienced professionals while contributing to real-world machine learning projects. We value individuals who are self-motivated, curious about AI/ML technologies, and passionate about transforming complex data into actionable insights. 

Expectation from this role:

• Work alongside senior team members to develop and deploy machine learning models that address business challenges  

• Assist in transforming business problems into technical data problems through collaboration with stakeholders 

• Support in building data preprocessing pipelines for structured and unstructured data  

• Learn and implement various modeling algorithms using machine learning techniques  

• Contribute to model monitoring, validation, and testing processes  

• Participate in code reviews and learn best practices for predictive analytics infrastructure 

• Demonstrate willingness to adapt quickly and wear multiple hats in our small, dynamic team  

• Show initiative in learning new technologies and frameworks as needed 

Required Skills and Qualifications:

Educational Background:

• Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or related field preferred. 

• Strong foundational knowledge in machine learning, statistics, and data analysis  

• Demonstrated learning through coursework, online courses, bootcamps, or self-study projects involving Python programming and data science libraries 

Technical Skills:

• Proficiency in Python with exposure to data science libraries such as NumPy, pandas, and scikit-learn  

• Understanding of fundamental machine learning algorithms (linear/logistic regression, decision trees, clustering)  

• Basic knowledge of data structures and algorithms  

• Familiarity with SQL for basic data querying  

• Exposure to version control systems like Git  

• Understanding of data visualization principles and libraries (Matplotlib, Seaborn)  

• Basic knowledge of probability and statistical concepts 

Data Science Fundamentals:

• Understanding of machine learning workflows: data preprocessing, feature engineering, model training, and evaluation  

• Knowledge of common data preprocessing techniques and handling missing data  

• Basic understanding of model evaluation metrics and cross-validation  

• Exposure to Jupyter notebooks for exploratory data analysis  

• Familiarity with data types and data structures in Python 

Soft Skills & Attitude:

• Strong problem-solving abilities and analytical thinking  

• Excellent learning agility and adaptability to new technologies  

• Eagerness to learn from senior team members and take constructive feedback  

• Ability to work independently on assigned tasks while knowing when to seek help  

• Strong communication skills to effectively collaborate with team members  

• Curiosity about emerging AI/ML technologies and industry trends 

Preferred Qualifications:

• Experience or coursework in Natural Language Processing (NLP) and familiarity with NLTK library  

• Personal projects or academic work demonstrating practical application of machine learning  

• Participation in kaggle competitions or similar data science challenges  

• Basic exposure to deep learning frameworks like TensorFlow or PyTorch  

• Understanding of cloud platforms (AWS, GCP, or Azure) at a beginner level  

• Knowledge of API development using Flask or FastAPI  

• Familiarity with Docker containers  

• Experience with data visualization tools like Tableau or Power BI  

• Contributions to open-source projects  

• Certifications in data science or machine learning from recognized platforms 

What Sets the Ideal Candidate Apart:

• Portfolio of personal projects showcasing ML applications, even if basic  

• Demonstrated ability to learn new technologies quickly and independently  

• Strong foundation in mathematics and statistics  

• Genuine passion for AI/ML with active engagement in the community (blogs, meetups, online courses)  

• Growth mindset and willingness to take on challenges beyond current skill level  

• Ability to explain technical concepts in simple terms  

• Proactive approach to problem-solving and debugging  

• Enthusiasm for working in a startup environment with evolving requirements