Machine Learning Engineer

This role is for one of Weekday’s clients
Min Experience: 0 years
Location: Bengaluru
JobType: full-time

Requirements

About the Role:
We are seeking a motivated and passionate Machine Learning Engineer to join our growing AI/ML team. This is an excellent opportunity for recent graduates or early-career professionals to work on real-world applications of Machine Learning (ML), Artificial Intelligence (AI), and Natural Language Processing (NLP) technologies. You'll be part of a team that builds intelligent systems to solve complex problems and deliver value to our customers across domains.

If you're a self-starter who’s eager to apply theoretical knowledge into practice, experiment with state-of-the-art tools like TensorFlow, and work collaboratively on challenging problems in NLP and AI, this role is for you.

Key Responsibilities:

• Assist in the development, training, and evaluation of machine learning models using Python and libraries such as TensorFlow and Scikit-learn.
• Support data collection, preprocessing, and transformation tasks to build robust ML pipelines.
• Collaborate with data scientists, software engineers, and product teams to understand problem requirements and deliver ML-based solutions.
• Work on natural language processing tasks such as text classification, sentiment analysis, named entity recognition, and language modeling.
• Implement ML models into production environments and monitor model performance.
• Conduct research and stay updated with the latest developments in AI/ML and NLP.
• Optimize and tune models for accuracy, speed, and scalability.
• Prepare documentation, reports, and presentations to communicate results and findings to stakeholders.

Required Skills:

• Basic understanding of machine learning concepts such as supervised/unsupervised learning, classification, regression, and clustering.
• Familiarity with Python programming and common ML libraries like TensorFlow, Keras, Scikit-learn, and Pandas.
• Exposure to natural language processing (NLP) tasks and basic algorithms.
• Understanding of data preprocessing, feature engineering, and model evaluation techniques.
• Enthusiasm to learn and work with deep learning models and frameworks.
• Strong analytical thinking and problem-solving skills.
• Good communication skills and the ability to work in a collaborative environment.

Nice to Have:

• Internship or project experience in ML, AI, or NLP.
• Knowledge of neural networks, RNNs, CNNs, or transformer models like BERT or GPT.
• Experience working with large datasets or on cloud platforms such as AWS, GCP, or Azure.
• Understanding of version control (Git) and deployment tools (Docker, MLflow, etc.).
• Participation in ML competitions (e.g., Kaggle) or open-source contributions.

Educational Qualification:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, or a related field.