AI/ML Python Developer

We are seeking a skilled and passionate AI/ML Python Developer to join our team and play a key role in building, training, and deploying intelligent models that solve real-world problems. You will move beyond experimentation to focus on the entire lifecycle of machine learning- from data pipeline to production API. This is an ideal role for a developer who thrives on turning data into robust, scalable AI solutions.

Key Responsibilities

• End-to-End Model Development: Design, build, train, evaluate, and optimize machine learning models (e.g., for NLP, Computer Vision, or predictive analytics) using Python and modern frameworks.

• Production Engineering & MLOps: Package, deploy, and maintain models in production environments. Develop APIs for model serving and implement monitoring for performance and drift.

• Robust Data & Code Practices: Build reliable data preprocessing and feature engineering pipelines. Write clean, maintainable, and well-documented code within a collaborative Git-based workflow.

• Collaboration & Solution Ownership: Work closely with data scientists, engineers, and product teams to understand requirements, iterate on solutions, and deliver measurable business impact.

Required Qualifications & Skills

• Must-Have Technical Expertise:

  • Strong proficiency in Python and its core data science stack (NumPy, Pandas, Scikit-learn).

  • Hands-on experience with deep learning frameworks, preferably PyTorch or TensorFlow.

  • Proven experience taking ML models from concept to production (familiarity with Docker, REST APIs/FastAPI/Flask, and basic cloud services).

  • Solid software engineering fundamentals (Git, code reviews, testing, debugging).

• Highly Valued Skills (Strong Pluses):

  • Experience with MLOps tools like MLflow, Kubeflow, or cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML).

  • Specialized knowledge in Natural Language Processing (NLP) using libraries like Hugging Face Transformers, or Computer Vision (CV) with OpenCV.

  • Experience building and orchestrating data pipelines (e.g., with Apache Airflow).

    Education & Experience

    • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field.

    • 3+ years of professional experience in a role focused on developing and deploying machine learning models with Python.