Description

About the Role

We are looking for an Applied Machine Learning Engineer who can build production-ready ML solutions for real business use cases. The role involves working across data preparation, model development, evaluation, deployment, and monitoring.
 

Responsibilities

• Develop machine learning solutions for classification, prediction, recommendation, NLP, or document-processing use cases.
• Prepare, clean, and analyse structured and unstructured datasets.
• Train, evaluate, optimise, and validate machine learning models.
• Build APIs and services for model inference.
• Deploy and monitor models in production.
• Improve model accuracy, reliability, latency, and scalability.
• Work with product and engineering teams to convert business requirements into ML solutions.
• Document experiments, datasets, assumptions, and results.

Required Skills

• 3–4 years of experience in applied machine learning.
• Strong proficiency in Python.
• Hands-on experience with scikit-learn, PyTorch, TensorFlow, or similar frameworks.
• Strong understanding of machine learning algorithms and evaluation metrics.
• Experience with Pandas, NumPy, SQL, and data-processing pipelines.
• Experience deploying models as APIs or production services.
• Working knowledge of Git, Docker, and cloud environments.
• Strong analytical and problem-solving skills.

Good to Have

• Experience with NLP, LLMs, RAG, computer vision, or document AI.
• Familiarity with vector databases and embedding models.
• Experience with MLOps, experiment tracking, and model monitoring.
• Exposure to AWS, Azure, or GCP

Key Skills

Education

Any Graduate