AI/ML Engineer
1 week ago
Key Responsibilities:
- Design and develop machine learning models and algorithms for different applications, such as computer vision, natural language processing, Large Language Model and predictive analytics.
- Must have experience in RAG Based applications
- Collect, preprocess, and analyze data from various sources to train and test machine learning models.
- Collaborate with cross-functional teams, such as software developers, data scientists, and business analysts, to define requirements and deliver solutions.
- Implement and optimize machine learning models on various platforms, such as cloud, edge devices, and embedded systems.
- Evaluate the performance of machine learning models using metrics such as accuracy, precision, recall, and F1 score.
- Use best practices for software engineering, such as version control, code review, and testing, to ensure high-quality and scalable solutions.
- Keep up-to-date with the latest research and trends in AI/ML and apply them to improve the performance and efficiency of machine learning models.
Requirements:
- Bachelor's or Master's degree in Computer Science or related fields.
- 3+ years of experience in AI/ML, with a focus on designing and developing machine learning models and algorithms.
- Strong programming skills in one or more languages such as Python, R, or MATLAB.- Python
- Experience with popular AI/ML frameworks such as TensorFlow, PyTorch, Keras, or scikit-learn. - he worked , know of Pytorch
- Experience in Web Frameworks like Django, Flask or Fast Api
- Experience with statistical modelling, NLP, LLM and computer vision. - Nlp know, computyert
- Knowledge of statistical analysis, linear algebra, calculus, hypothesis testing, and probability theory.
- Experience with data preprocessing, data visualization, and data analysis tools such as Pandas, NumPy, and Matplotlib.
- Strong problem-solving skills and the ability to work independently and as part of a team.
- Excellent communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Preferred:
- Experience with distributed computing, parallel processing, and cloud computing platforms such as AWS, Azure, or Google Cloud.-aws
- Experience with computer vision, natural language processing, or time-series analysis.
- Experience with software engineering best practices such as agile development, continuous integration, and deployment.
- Experience with data management and SQL databases.
- Experience with python data scraping packages like requests, selenium, scrapy.
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