Data Engineer (Python, NLP, ML)

We are seeking a skilled 2+years Data Engineer proficient in Python, with a strong background in Natural Language Processing (NLP) and Machine Learning (ML). As a Data Engineer, you will be responsible for designing, developing, and maintaining data pipelines and systems to support our NLP and ML initiatives. You will work closely with our data scientists and software engineers to deploy robust, scalable solutions that leverage cutting-edge NLP and ML techniques. Responsibilities: Develop and maintain data pipelines to ingest, process, and analyze large volumes of text data. Implement NLP algorithms and techniques for tasks such as text classification, named entity recognition, sentiment analysis, and topic modeling. Collaborate with data scientists to integrate NLP and ML models into production systems. Optimize data processing and model inference pipelines for performance and scalability. Design and implement data storage solutions that support efficient access and retrieval of structured and unstructured data. Work with cross-functional teams to understand requirements and translate them into technical solutions. Stay updated on the latest developments in NLP and ML research and technology. Requirements: Bachelor's degree or higher in Computer Science, Engineering, or related field. Strong proficiency in Python programming and experience with relevant libraries (e.g., NLTK, spacey, sickie-learn, Tensor Flow, PyTorch). Solid understanding of NLP concepts and techniques, including tokenization, word embeddings, and text preprocessing. Experience with building and optimizing data pipelines using tools such as Apache Spark, Kafka, or Airflow. Familiarity with cloud platforms such as AWS, Azure, or GCP, and their data services (e.g., S3, Big Query, Dataflow). Knowledge of database systems (e.g., SQL, NoSQL) and experience with data modeling and schema design. Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment. Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders. Experience with version control systems (e.g., Git) and agile development methodologies is a plus. Benefits: Competitive salary and benefits package. Opportunity to work on challenging problems at the intersection of NLP and ML. Collaborative and inclusive work environment. Professional development opportunities and support for continued learning.