Job Type
Full-time
Description
About the RoleThe
Software Engineer - AI & Machine Learning is responsible for designing, developing, and maintaining modern software applications that leverage
machine learning, natural language processing (NLP), clustering algorithms, and Generative AI to automate defect analysis and improve operational intelligence.
In this role, you will build scalable software solutions that reduce manual intervention in diagnostics, enhance operational efficiency, and deliver intelligent automation across aviation maintenance workflows. You will collaborate closely with Engineering, Product, QA, and Operations teams to develop AI-powered capabilities that directly impact customer outcomes.
Job Duties- Design, develop, and maintain scalable software applications using Python and modern web frameworks such as Django, Flask, or FastAPI.
- Develop and enhance machine learning models, clustering algorithms, and NLP solutions for automated defect analysis and pattern recognition.
- Build AI-powered diagnostic systems that intelligently classify, categorize, and route operational tickets.
- Design, optimize, and maintain SQL databases, queries, and data models that support large-scale analytics and real-time processing.
- Develop and maintain RESTful APIs supporting AI-powered applications and enterprise integrations.
- Improve clustering logic to reduce manual intervention in defect categorization and operational workflows.
- Collaborate with Product Management, QA, Engineering, and Operations teams to translate business requirements into scalable technical solutions.
- Research, evaluate, and implement emerging AI, machine learning, and software engineering technologies that improve product capabilities.
- Participate in Agile ceremonies including sprint planning, code reviews, retrospectives, and technical design discussions.
- Continuously improve application performance, scalability, maintainability, and software quality.
- Document technical designs, AI models, engineering standards, and development best practices.
Requirements
- 4-8+ years of experience in software development using Python and modern web frameworks.
- Strong proficiency with SQL, database design, query optimization, indexing, and performance tuning.
- Hands-on experience with machine learning frameworks including Scikit-learn, TensorFlow, PyTorch, Pandas, and NumPy.
- Strong experience developing clustering algorithms including K-Means, DBSCAN, and Hierarchical Clustering.
- Experience building Natural Language Processing (NLP) solutions including text classification, entity extraction, sentiment analysis, and language models.
- Experience with Generative AI concepts and AI-assisted software development workflows.
- Strong understanding of feature engineering, data preprocessing, model validation, and model optimization.
- Experience designing, developing, and consuming REST APIs.
- Knowledge of data pipeline architecture, ETL processes, and real-time data processing.
- Experience working with relational and NoSQL databases supporting analytics workloads.
- Familiarity with Git, CI/CD pipelines, automated testing, and modern DevOps practices.
- Bachelor's degree in Computer Science, Computer Engineering, Data Science, Machine Learning, Artificial Intelligence, or a related technical field.
Preferred Skills- Experience developing AI solutions for predictive maintenance, defect analysis, operational intelligence, or industrial automation.
- Experience with LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, vector databases, embeddings, or semantic search.
- Experience working with cloud AI platforms such as Azure AI, AWS AI/ML, or Google Vertex AI.
- Experience building scalable ML pipelines using MLOps principles.
- Familiarity with containerization technologies such as Docker and orchestration platforms such as Kubernetes.
- Experience working in Agile/Scrum software development environments.
- Strong analytical thinking, troubleshooting, and problem-solving skills.
- Excellent communication skills with the ability to explain complex technical concepts to technical and non-technical stakeholders.
- Passion for continuous learning and adopting emerging AI technologies to solve real-world business challenges.
