Job Title: Senior AI Engineer
Scope: Senior AI Engineer will take the lead in designing developing and deploying advanced AI solutions with a focus on NLP and LLM technologies. This role requires a seasoned professional capable of working on complex AI projects that involve training and finetuning largescale language models developing NLP pipelines and deploying these models at scale.
You will collaborate closely with our AI research data science and software engineering teams to drive innovation and implement AI solutions that improve customer experiences optimize operations and fuel business growth.
Responsibilities:
- Lead AI Projects: Design develop and implement advanced AI solutions focused on NLP and LLM technologies to solve realworld problems.
- Model Development: Build finetune and deploy largescale language models (such as GPT BERT etc.) for various applications including text classification question answering summarization machine translation and chatbots.
- NLP Pipeline: Develop and optimize NLP workflows such as tokenization text preprocessing and feature extraction using libraries like spaCy NLTK or Hugging Face.
- Model Training & FineTuning: Train custom LLMs and NLP models leverage transfer learning and optimize models for inference speed and accuracy.
- Performance Optimization: Implement scalable solutions that optimize the performance of LLMs in production environments including managing large datasets and improving model throughput.
- Collaboration: Work crossfunctionally with data scientists machine learning engineers and software engineers to integrate AI models into our platform.
- Research & Innovation: Stay uptodate with the latest advancements in NLP and AI and incorporate stateoftheart techniques into our products.
Mentorship: Mentor junior team members and provide technical leadership in AIrelated projects.
Qualifications:
- Experience: 2:4 years of experience in AI with a strong focus on NLP and LLM.
- Experience with reinforcement learning (RL) for NLP tasks.
- Familiarity with multimodal models and techniques.
- Knowledge of data annotation and labeling tools.
- Contributions to AI research in academic journals or conferences.
- Experience with MLOps practices to streamline model deployment and monitoring
Benefits:
- Competitive salary.
- Health insurance.
- Professional development opportunities.
- Flexible working hours.
- Collaborative and supportive work environment.
Working Conditions:
Working Hours: 9 AM6 PM ( SundayThursday ).
Working Model: Hybrid