Software Engineer (AI & Machine Learning)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Software Engineer (AI & Machine Learning): Designing and developing scalable software applications that leverage machine learning, NLP, and Generative AI to automate defect analysis and operational intelligence. Focus on building intelligent diagnostic systems, optimizing data pipelines, and integrating AI-powered capabilities into aviation maintenance workflows.
Location: Must be based in the USA
Company
is a leading software provider enabling aviation teams worldwide to improve operational efficiency and safety through customer-driven innovation.
What you will do
- Design and develop scalable software applications using Python and modern web frameworks.
- Develop and enhance machine learning models, clustering algorithms, and NLP solutions for defect analysis.
- Build AI-powered diagnostic systems to classify and route operational tickets.
- Design and maintain SQL databases and data models for large-scale analytics.
- Develop RESTful APIs to support AI-powered applications and enterprise integrations.
- Collaborate with cross-functional teams to translate business requirements into technical solutions.
Requirements
- 4–8+ years of experience in software development with Python.
- Strong proficiency in SQL, database design, and query optimization.
- Hands-on experience with ML frameworks like Scikit-learn, TensorFlow, PyTorch, Pandas, and NumPy.
- Experience with clustering algorithms (K-Means, DBSCAN) and NLP solutions.
- Understanding of feature engineering, model validation, and Generative AI concepts.
- Must be based in the USA.
Nice to have
- Experience with LLMs, RAG, and vector databases.
- Knowledge of MLOps principles and cloud AI platforms (AWS, Azure, GCP).
- Familiarity with Docker and Kubernetes.
- Background in predictive maintenance or industrial automation.
Culture & Benefits
- Focus on AI-forward innovation and creative problem-solving.
- Collaborative environment centered on customer outcomes.
- Commitment to continuous learning and adopting emerging technologies.
- Agile development culture with emphasis on code quality and best practices.
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