Machine Learning Engineer - Python

Qcentrio is actively seeking a skilled Machine Learning Engineer with expertise in Python to join our innovative AI/ML team. You'll be responsible for the end-to-end lifecycle of machine learning models, from design and development to deployment and performance tuning. The ideal candidate will have strong data analysis capabilities, experience with web frameworks like Flask, and a passion for building scalable and intelligent solutions.

Responsibilities

• Model Development & Deployment: Design, develop, and deploy machine learning models and algorithms to address diverse business challenges.
• Data Analysis & Feature Engineering: Perform in-depth data analysis to extract insights, identify patterns, and develop and implement robust feature engineering processes to enhance model performance.
• Cross-functional Collaboration: Collaborate closely with data scientists and other cross-functional teams to understand business requirements and translate them into effective technical solutions.
• Infrastructure & Applications: Build and maintain scalable data pipelines and infrastructure. Develop and deploy machine learning applications using Python web frameworks such as Flask, FastAPI, or Django.
• Model Evaluation & Tuning: Conduct thorough experiments, perform model tuning, and evaluate model performance using appropriate metrics to ensure optimal results.

Must-Have Skills

• Python Proficiency: Strong expertise in Python and its essential libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow, PyTorch).
• Web Frameworks: Experience with web frameworks such as Flask, FastAPI, or Django.
• ML Fundamentals: Strong understanding of core machine learning algorithms and techniques.
• Data Visualization: Proficiency with data visualization tools (e.g., Matplotlib, Seaborn).
• Problem-Solving: Strong problem-solving skills and the ability to work effectively both independently and as part of a team.
• Communication: Excellent communication skills to effectively convey complex technical concepts to non-technical stakeholders.

Good-to-Have Skills

• Experience with cloud platforms, particularly AWS.
• Knowledge of MLOps practices and tools.
• Experience with Natural Language Processing (NLP) techniques.
• Exposure to Generative AI (GenAI) technologies.