Machine Learning Engineer

Role & responsibilities

• Collaborate with domain experts and stakeholders to understand business challenges and requirements to be supported by NLP/ML.

• Develop and implement machine learning models and algorithms using NLP techniques, such as text classification, sentiment analysis, named entity recognition, and topic modeling, to solve specific business problems.
• Perform data analysis and pre-processing tasks, including data cleaning, feature engineering, and data transformation, to prepare data for machine learning models.
• Evaluate and optimize the performance of machine learning models using appropriate metrics and techniques and iterate on model design and implementation as needed.
• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate machine learning models into our products and services.
• Stay up to date with the latest advancements in machine learning, NLP, and related technologies, and proactively apply them to solve business challenges.
• Ensure compliance with data privacy and security requirements throughout the machine learning development process

Preferred candidate profile

• Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.

• More than 4 years of experience in machine learning, natural language processing, and related technologies, with a strong understanding of NLP concepts and techniques.
• Hands-on experience in developing and implementing machine learning models using libraries such as TensorFlow, Keras, PyTorch, or scikit-learn.
• Proficiency in programming languages such as Python or Java, and experience with data manipulation and analysis using tools such as Pandas, NumPy, or SQL.
• Strong understanding of statistical concepts and machine learning algorithms, including supervised and unsupervised learning, feature selection, model evaluation, and model deployment.
• Experience with NLP techniques, such as text preprocessing, tokenization, POS tagging, word embeddings, and sentiment analysis.
• Strong problem-solving skills, ability to work independently and in a team, and excellent communication skills.
• Familiarity with cloud-based machine learning platforms, such as AWS, Google Cloud, or Azure, is a plus.
• Experience in working with large-scale datasets and big data technologies, such as Hadoop or Spark, is a plus.

If you are a skilled Machine Learning Engineer with a passion for natural language processing, and you enjoy working closely with domain experts to develop cutting-edge solutions, we would love to hear from you. Apply now to join our team and help us shape the future of machine learning-powered products

What we value

• Accountability: A proactive approach to taking full ownership of tasks and delivering exceptional outcomes.

• Independence: The ability to work autonomously while achieving project goals and adhering to timelines.

• Creative Problem-Solving: Innovative thinking and the ability to translate complex ideas into impactful visuals.