Senior Machine Learning Engineer - NLP

Roles and Responsibilities :

• Big picture: Understand customers’ needs and innovate and use cutting edge Machine Learning techniques to build data-driven solutions.
• Work on NLP problems across areas such as text classification, entity extraction, summarization, generative NLP,  and others.
• Collaborate with cross-functional teams to integrate/upgrade AI solutions into company’s products and services.
• Optimize existing machine learning models or performance, scalability and efficiency.
• Build, deploy and own scalable production NLP pipelines.
• Build post-deployment monitoring and continual learning capabilities. Propose suitable evaluation metrics and establish benchmarks.
• Keep abreast with SOTA techniques in your area and exchange knowledge with colleagues.
• Desire to learn, implement and apply latest emerging model architectures (like LLMs), inference optimizations, distributed training, using open-source models, etc.

We'll love to explore more about you if you have :

• Bachelors in Computer Science or Mathematics related fields with 4+ years of experience in Machine Learning and NLP.
• Proficient in Python, RAG, Knowledge Graphs.
• Knowledge and practical experience in solving NLP problems in areas such as text classification, entity tagging, information retrieval, question-answering, natural language generation, clustering, etc.
• Knowledge and experience with data engineering, basic machine learning concepts, data mining, feature extraction, pattern recognition, etc.
• Knowledge and hands-on experience with Transformer-based Language Models like BERT, DeBERTa, Flan-T5, GPT, Llama, etc.
• Deep familiarity with internals of at least a few Machine Learning algorithms and concepts.
• Experience with Deep Learning frameworks like Pytorch and common machine learning libraries like scikit-learn, numpy, pandas, NLTK, etc.
• Experience with ML model deployments using REST API, Docker, Kubernetes, etc.
• Knowledge of cloud platforms (AWS/Azure/GCP) and their machine learning services is desirable.
• Knowledge of basic Data Structures and Algorithms.
• Knowledge of real-time streaming tools/architectures like Kafka, Pub/Sub is a plus.