Python with AI/ML Developer

We are looking for a resilient, forward-thinking Python Developer with expertise in AI and Machine Learning deployment to join our growing technology team. As part of this role, you will be responsible for building, deploying, and maintaining scalable ML models and backend systems that support AI-driven products. This role requires a passion for innovation, an eye for detail, and the ability to translate complex problems into effective technical solutions.

A successful candidate will be deeply familiar with Python, AI/ML frameworks, deployment strategies, and production-level best practices. You will work closely with cross-functional teams to ensure that our AI solutions are efficient, scalable, and aligned with user needs and business goals.

Responsibilities:

• Develop, test, and deploy machine learning models using Python and AI frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Collaborate with data scientists, product teams, and engineers to translate prototypes into production-ready systems.
• Build and manage APIs and backend services using Flask, FastAPI, or similar frameworks.
• Deploy ML models into cloud or on-prem environments using Docker, Kubernetes, and CI/CD pipelines.
• Monitor and optimize model performance, latency, and resource usage post-deployment.
• Automate data preprocessing, feature engineering, and model training workflows.
• Write clean, maintainable, and scalable code with a strong focus on quality and performance.
• Stay current with the latest research and best practices in AI, ML, and MLOps.
• Troubleshoot and resolve issues related to ML model performance, deployment, and data pipelines.
• Document technical architecture, processes, and best practices for internal teams.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• 2+ years of experience in Python development with a focus on AI/ML projects.
• Strong knowledge of ML/AI tools and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience deploying and maintaining ML models in production environments.
• Proficiency with containerization (Docker) and familiarity with orchestration tools (Kubernetes is a plus).
• Knowledge of REST APIs and microservice architecture.
• Experience working with cloud platforms (AWS, Azure, or GCP).
• Strong problem-solving skills and a proactive, team-oriented mindset.
• Version control with Git and collaboration using GitHub or GitLab.
• Understanding of MLOps workflows and model lifecycle management.

Preferred Skills:

• Experience with data streaming platforms (Kafka, Apache Spark).
• Familiarity with MLflow, Airflow, DVC, or similar MLOps tools.
• Exposure to computer vision, NLP, or deep learning projects.
• Knowledge of database systems (vector).
• Knowledge of LLM.
• Experience building interactive dashboards using Streamlit, Dash, or Plotly.
• Contributions to open-source AI/ML projects or participation in Kaggle competitions.