Responsibilities:<\/span><\/b>
<\/p>
- Creates machine learning models and utilizes data to train models<\/span>
<\/span><\/li>
- Focuses on analyzing data to find relations between the input and the desired output<\/span>
<\/span><\/li>
- Understands business objectives and develops models that help achieve them, along with metrics to track their progress<\/span>
<\/span><\/li>
- Designs and develops machine learning and deep learning systems<\/span>
<\/span><\/li>
- Runs machine learning tests and experiments Implements appropriate machine learning algorithms<\/span>
<\/span><\/li>
<\/ul>
<\/p>
General Skills:<\/b>
<\/p>
- Experience managing available resources such as hardware, data, and personnel so that deadlines are met
<\/span><\/li>
- Experience analyzing the machine learning algorithms that could be used to solve a given problem and ranking them by their success probability
<\/span><\/li>
- Experience exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
<\/span><\/li>
- Experience verifying data quality, and\/or ensuring it via data cleaning
<\/span><\/li>
- Experience supervising the data acquisition process if more data is needed
<\/span><\/li>
- Experience finding available datasets online that could be used for training
<\/span><\/li>
- Experience defining validation strategies
<\/span><\/li>
- Experience defining the preprocessing or feature engineering to be done on a given dataset
<\/span><\/li>
- Background in statistics and computer programming
<\/span><\/li>
- A team player with a track record for meeting deadlines, managing competing priorities and client relationship management experience.
<\/span><\/li>
<\/ul>
<\/div><\/span>
Requirements<\/h3>
Experience and Skill Set Requirements:<\/span><\/u><\/b>
<\/p>Must Haves:<\/span><\/u><\/b>
<\/p>
- Deep Understanding of Machine Learning Concepts: Proficiency in fundamental machine learning concepts, algorithms, and techniques.<\/span>
<\/li>
- Expertise in Natural Language Processing (NLP): Knowledge of NLP techniques and models, especially BERT and other transformer\-based models, for tasks like text classification, sentiment analysis, and language understanding.<\/span>
<\/li>
- Experience with Deep Learning Frameworks: Proficiency in deep learning libraries such as TensorFlow or PyTorch. Experience with implementing, training, and fine\-tuning BERT models using these frameworks is crucial.<\/span>
<\/li>
- Data Preprocessing Skills: Ability to perform text preprocessing, tokenization, and understanding of word embeddings.<\/span>
<\/li>
- Programming Skills: Strong programming skills in Python, including experience with libraries like NumPy, Pandas, and Scikit\-learn.<\/span>
<\/li>
- Model Optimization and Tuning: Skills in optimizing model performance through hyperparameter tuning and understanding of trade\-offs between model complexity and performance.<\/span>
<\/li>
- Understanding of Transfer Learning: Knowledge of how to leverage pre\-trained models like BERT for specific tasks and adapt them to custom datasets.<\/span>
<\/li>
<\/ul> <\/span>
<\/p>Skill Set Requirements:<\/span><\/u><\/b>
<\/p>
- Deep Understanding of Machine Learning Concepts:<\/span><\/b> Proficiency in fundamental machine learning concepts, algorithms, and techniques.<\/span>
<\/li>
- Expertise in Natural Language Processing (NLP): Knowledge of NLP techniques and models, especially BERT and other transformer\-based models, for tasks like text classification, sentiment analysis, and language understanding.<\/span>
<\/li>
<\/ul>
- Experience with Deep Learning Frameworks:<\/span><\/b> Proficiency in deep learning libraries such as TensorFlow or PyTorch. Experience with implementing, training, and fine\-tuning BERT models using these frameworks is crucial.<\/span>
<\/li>
<\/ul>
- Data Preprocessing Skills:<\/span><\/b> Ability to perform text preprocessing, tokenization, and understanding of word embeddings.<\/span>
<\/li>
- Programming Skills:<\/span><\/b> Strong programming skills in Python, including experience with libraries like NumPy, Pandas, and Scikit\-learn.<\/span>
<\/li>
<\/ul>
- Model Optimization and Tuning:<\/span><\/b> Skills in optimizing model performance through hyperparameter tuning and understanding of trade\-offs between model complexity and performance.<\/span>
<\/li>
<\/ul>
- Understanding of Transfer Learning:<\/span><\/b> Knowledge of how to leverage pre\-trained models like BERT for specific tasks and adapt them to custom datasets.<\/span>
<\/li>
<\/ul>
<\/div><\/span>
<\/body>
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