Machine Learning Engineer - NLP / Computer Vision

Job Description :

We are seeking a creative and experienced Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in developing and deploying NLP and computer vision models, deep learning, and API creation. You will be responsible for innovating and exploring new models to accomplish complex tasks and improve our product offerings.

• Design, develop, and deploy machine learning models with a focus on Natural Language Processing (NLP) and Computer Vision.
• Perform data labelling and preprocessing to prepare datasets for training.
• Select appropriate deep learning models and algorithms to solve specific problems.
• Train, fine-tune, and validate models to achieve high accuracy and performance.
• Build APIs for integrating machine learning models into existing applications.
• Continuously explore and evaluate new machine learning techniques and models to enhance our capabilities.
• Collaborate with cross-functional teams to understand business needs and provide AI-driven solutions.
• Document and present model development processes, results, and insights to stakeholders.
• Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
• Proven experience in developing and deploying machine learning models, particularly in NLP and Computer Vision.
• 3 or 3+ years of experience in Artificial Intelligence and Machine Learning.
• Proficiency in programming languages such as Python, and experience with machine learning libraries / frameworks like TensorFlow, PyTorch, and scikit-learn.
• Strong understanding of deep learning techniques and algorithms.
• Experience with data preprocessing and data labelling.
• Ability to build and deploy APIs for machine learning models.
• Excellent problem-solving skills and attention to detail.
• Strong communication skills and the ability to work well in a team environment
• Experience with cloud platforms such as AWS, Google Cloud, or Azure.
• Familiarity with big data technologies like Hadoop or Spark.
• Knowledge of additional programming languages such as R, Java, or C++.
• Understanding of MLOps and model deployment pipelines.

ref : hirist.tech)