Machine Learning Engineer - Python

Machine Learning Engineer

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.