Applied Scientist

Location:

About Us

At Neural Nurture, we are committed to advancing the frontiers of Artificial Intelligence and Machine Learning. Our research lab focuses on solving some of the most exciting and challenging problems in Machine Learning, Natural Language Processing, and Computer Vision.

Role Overview

Natural Language Processing

Areas of focus could be one or more of the following:

• General Machine Learning: Advancing core ML techniques to improve model efficiency, reliability, and scalability across domains.
• Computer Vision (CV): Developing robust visual understanding systems for real-world image and video analysis.
• Natural Language Processing (NLP): Building intelligent language models for tasks such as understanding, summarization, and information extraction.
• Multimodal Learning: Creating models that effectively integrate and reason over text, vision, and other data modalities.

Responsibilities

• Collaborate with research mentors to brainstorm and define solutions for challenging real-world problems.
• Review relevant literature and existing approaches to identify gaps and opportunities for innovation.
• Design novel solutions, build working prototypes, and perform comprehensive experiments to assess the effectiveness of the proposed methods against relevant benchmarks.
• Evaluate results of experiments, validate findings, and fine-tune models based on insights gained.
• Present research results with other internal teams or at external academic or industry events, effectively communicating technical findings.
• Prepare and refine research papers for submission to leading conferences in Machine Learning, Natural Language Processing, and Computer Vision.

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, Applied Mathematics, or a related field.
• Proficiency in programming languages such as Python, Java, C++, or other relevant languages.
• Strong foundational knowledge of core machine learning concepts and the mathematical principles underlying ML algorithms.
• Experience with Deep Learning frameworks (e.g., PyTorch, TensorFlow).
• Hands-on experience in one or more of the following: NLP (Transformers, LLM fine-tuning, prompt engineering), CV (CNNs, ViTs, object detection, panoptic segmentation, robustness techniques, diffusion models).
• Strong analytical thinking and ability to communicate technical ideas clearly
• Ability to work independently and collaboratively in a fast-paced environment.
• Passion for research and a curiosity-driven mindset.

Preferred Qualifications

• Strong coding skills in Python.
• Prior research experience including publications in major conferences or journals.
• Familiarity with linguistic theory, structured prediction models, or human-centered evaluation methodologies.
• Prior experience in research projects related to language model evaluation, interpretability, or structured learning.
• Familiarity with computer vision robustness concepts such as corruptions, adversarial attacks, and distribution shifts
• Experience working with Vision-Language Models or Multimodal Learning (e.g., CLIP, BLIP, Flamingo, LLaVA) is a plus
• Familiarity with libraries like Hugging Face Transformers.
• Experience working with large-scale datasets and training models on cloud or cluster environments.

Why Join Neural Nurture?

At Neural Nurture, you will have the opportunity to work closely with experienced researchers specializing in ML, Natural Language Processing, and Computer Vision. Our collaborative environment fosters deep technical learning and hands-on mentorship, helping you grow as a researcher. Employees at Neural Nurture are encouraged to contribute to cutting-edge projects aimed at both academic advancement and real-world impact, with opportunities to publish in top-tier ML, NLP, and CV conferences. You will tackle challenging problems at the intersection of academic research and industry applications, gaining valuable experience that prepares you for future careers in research, academia, or industry.

Application deadline:

Compensation: