About the Role:

We are looking for an experienced AI/ML Engineer with strong expertise in Python development, machine learning engineering, backend development, and cloud-based application deployment. The ideal candidate will have hands-on experience developing and deploying scalable AI/ML solutions, building microservices, and integrating machine learning models into enterprise applications.

Key Responsibilities:

- Design, develop, test, and deploy scalable Artificial Intelligence and Machine Learning solutions into production environments.

- Architect and implement end-to-end machine learning pipelines to automate data processing, model training, and deployment workflows.

- Develop and maintain high-performance backend microservices to serve AI/ML models.

- Build scalable APIs and integrate machine learning models into existing enterprise applications.

- Develop backend services using Python frameworks such as Django and FastAPI.

- Collaborate with engineering teams to integrate AI/ML capabilities into enterprise software ecosystems.

- Optimize CI/CD pipelines to streamline application and ML model deployment.

- Monitor model performance in production environments and identify opportunities for optimization and improvement.

- Implement model monitoring and retraining strategies to maintain model accuracy and reliability.

- Work with cloud platforms and containerized applications to support scalable deployments.

- Troubleshoot application, integration, and production issues.

- Follow software engineering best practices to ensure code quality, scalability, and maintainability.

Required Skills & Qualifications:

- 5 - 12 years of experience in Python development, AI/ML engineering, or related software engineering roles.

- Strong proficiency in Python programming.

- Hands-on experience with Django and FastAPI.

- Experience developing and maintaining REST APIs and microservices.

- Strong understanding of Machine Learning concepts and model deployment.

- Experience building and managing end-to-end ML pipelines.

- Knowledge of data structures, algorithms, and problem-solving techniques.

- Strong SQL skills, including writing and optimizing complex queries.

- Experience with cloud platforms such as AWS, GCP, or Microsoft Azure.

- Hands-on experience with Docker and containerized applications.

- Familiarity with CI/CD pipelines and automation practices.

- Understanding of distributed systems, scalability, and high-availability application design.

Good to Have:

- Experience with Generative AI and Large Language Models (LLMs).

- Knowledge of LangChain, RAG, prompt engineering, and vector databases.

- Familiarity with PyTorch, TensorFlow, or Scikit-learn.

- Experience with Kubernetes and cloud-native deployments.

- Knowledge of Kafka and event-driven architectures.

- Exposure to model monitoring, model drift detection, and MLOps practices.

- Experience with Git and Agile/Scrum methodologies.

Education:

- Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Engineering, or a related discipline.

Preferred Candidate Profile:

- Strong software engineering and analytical skills.

- Ability to develop production-ready AI/ML applications.

- Experience collaborating with cross-functional engineering and product teams.

- Strong communication, debugging, and problem-solving abilities.

- Availability: Immediate joiners or candidates serving notice with a last working day by the end of the month are preferred.