Associate ML Engineer

Vakansiyanın detalları

Design, develop, and optimize LLMs and NLP models for various applications, such as text classification, named entity recognition, sentiment analysis, and question answering.
Support data preprocessing workflows, including data cleaning, normalization, tokenization, and basic annotation tasks.
Fine-tune pre-trained LLMs (e.g., GPT, BERT, T5) on specific tasks using domain-specific data.
Work closely with cross-functional teams to integrate NLP solutions into products and services.
Continuously monitor, evaluate, and improve the performance of deployed models, addressing issues such as bias, fairness, and accuracy.
Contribute to the development and maintenance of NLP pipelines and workflows, including data preprocessing, model training, and inference.
Design and develop retrieval algorithms and models, including TF-IDF, BM25, and vector-based methods, to enhance search relevance and efficiency.
Design, develop, and optimize hybrid workflows integrating LLMs with retrieval algorithms.
Write clean, modular code and follow established coding standards for ML projects.
Collaborate with web and backend developers to help integrate ML services and APIs into applications.

Bachelor’s degree in Computer Science, Data Science, Applied Mathematics, or a related field. A Master’s degree is a plus.
1-2 years of experience in machine learning and NLP, with experience in LLMs and retrieval systems.
Knowledge of transformer architectures and experience implementing them in NLP tasks.
Experience with data preprocessing techniques for text data, including tokenization, stemming, lemmatization, and handling imbalanced datasets.
Strong understanding of deep learning frameworks like TensorFlow or PyTorch.
Experience with search engine frameworks such as Elasticsearch, Solr, or Lucene.
Knowledge of indexing techniques and data structures used in search engines.
Experience with query parsing, term weighting, and relevance feedback mechanisms.
Familiarity with cloud platforms (AWS, Google Cloud, Azure) for training and deploying LLMs.
Excellent problem-solving skills with the ability to innovate and experiment
Collaborative mindset with the ability to work effectively in cross-functional teams.