Machine Learning Engineer - NLP

Level Ai

2 - 7 years

40 - 45 Lacs

noida

Posted:1 week ago| Platform:

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Skills Required

computer science machine learning data structures information retrieval silicon pattern recognition open source data mining monitoring python

Work Mode

Work from Office

Job Type

Full Time

Job Description

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, summarisation, generative NLP, and others.
Collaborate with cross-functional teams to integrate/upgrade AI solutions into company s products and services Optimise existing machine learning models for 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 of 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.

Well love to explore more about you if you have:

Bachelors in Computer Science or mathematics-related fields with 2+ years of experience in Machine Learning and NLP.
Proficient in Python, NLP 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, Gemma, DeepSeek, etc.
Deep familiarity with Model Training concepts, model inference optimisations, GPUs, etc.
Experience with Deep Learning frameworks like Pytorch and common machine learning libraries like scikit-learn, numpy, pandas, NLTK, transformers, 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.

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