Intetics Inc., a leading global technology company providing custom software application development, distributed professional teams, software product quality assessment, and “all-things-digital” solutions, is looking for a AI/ML Engineer to enrich its team with a skilled professional to spread the company’s ideas, vision, content, and messages.
We are looking for an AI/ML Engineer to join our team. In this role, you will be responsible for designing, developing, and implementing machine learning models and AI solutions. You will work closely with cross-functional teams to deliver scalable and robust AI-driven applications. The ideal candidate will have a strong background in machine learning, data science, and software development.
Responsibilities:
- Design, develop, and implement AI and machine learning models
- Collaborate with cross-functional teams to define project requirements and deliverables
- Write clean, maintainable, and efficient code
- Perform data analysis and preprocessing to support AI/ML models
- Train and evaluate machine learning models using appropriate techniques and tools
- Deploy and maintain AI/ML models in production environments
- Stay updated with the latest industry trends and technologies in AI/ML
Requirements:
- Proven experience as an AI/ML Engineer or similar role
- Proficiency in one or more of the following programming languages and technologies:
- Python, R
- TensorFlow, PyTorch, Keras
- Scikit-learn, XGBoost, LightGBM
- Natural Language Processing (NLP) libraries (SpaCy, NLTK, Transformers)
- Deep learning frameworks
- SQL and NoSQL databases
- Cloud services (AWS, Azure, Google Cloud)
- Data visualization tools (Matplotlib, Seaborn, Tableau)
- Version control (Git)
- Strong problem-solving skills and attention to detail
- Excellent communication and teamwork abilities
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent experience)
Preferred Qualifications:
- Experience with big data technologies (Hadoop, Spark)
- Knowledge of microservices architecture
- Familiarity with DevOps practices and MLOps
