AI Machine Learning Engineer/AIML Engineer (German speaking)

AI Machine Learning Engineer/AIML Engineer (German speaking)

• At least having 4-6 years of experience in AIML
• Machine Learning Algorithms: Understanding of machine learning algorithms, especially deep learning models like Transformers, is crucial. This can include various types of neural networks, optimization techniques, and loss functions.
• Natural Language Processing (NLP): Knowledge of NLP techniques, text representation methods, and language models.
• Programming Languages: Proficiency in languages commonly used in machine learning such as Python/R/Java/Node.
• Library/Framework Proficiency: Familiarity with machine learning libraries like TensorFlow, PyTorch, Keras or or Scikit-learn.
• High-Performance Computing: Understanding of parallel computing, GPU acceleration, and distributed systems for training large models.
• Data Manipulation and Analysis: Skills in data pre-processing, transformation, and analysis are crucial, often involving libraries like Pandas, NumPy, or specialized tools for handling large datasets.
• DevOps and Infrastructure: Knowing how to set up and maintain machine learning pipelines, from data collection to model training to inference, possibly using cloud platforms like AWS, GCP, or Azure.
• Optimization: Understanding of both algorithmic and hardware optimization techniques to make training and inference more efficient.
• Version Control: Proficiency with version control systems like Git to manage codebase changes.
• Experience in REST API development, NoSQL database design, and RDBMS design and optimizations
• Excellent problem-solving skills and a collaborative mindset.
• Strong communication skills to work effectively with diverse teams