Asianet News - Lead Artificial Intelligence Engineer - NLP/LLM (5-7 yrs)

Job Description :

Job Title : Lead AI Engineer (Strategic Initiatives)

Experience : 5+ years in AI/ML, LLMs & App Development Experience OR 3+ Years working on NLP, LLMs model development & Fine-Tuning

Location : Bangalore / In-Office

Job Description :

We seek a highly skilled AI Engineer to join our strategic team and contribute to developing cutting-edge AI applications to work on multiple AI products, including D2C, Content and Search/ Discovery. The ideal candidate will have a strong foundation in machine learning, deep learning, and natural language processing. You will be responsible for designing, developing, and deploying innovative AI solutions that enhance user experience and drive business growth.

Key Responsibilities :

1. AI Model Development :

- Design, develop, and fine-tune AI models for various applications, including recommendation systems, content personalization, and automated content generation.

- Experiment with different architectures, algorithms, and hyperparameters to optimize model performance.

2. Natural Language Processing :

- Develop NLP-based solutions for sentiment analysis, text summarization, and chatbots.

- Leverage large language models (LLMs) to improve the quality and relevance of content recommendations.

3. Cloud Deployment and Operations :

- Deploy and manage AI models on cloud platforms (AWS, Azure, Google Cloud).

- Monitor model performance, identify issues, and implement optimizations.

- Collaborate with DevOps teams to ensure smooth deployment and scaling of AI applications.

4. Data Engineering and Analysis :

- Work with large datasets to extract meaningful insights and train AI models.

- Develop data pipelines to efficiently process and clean data.

5. Market Research and Vendor Evaluation :

- Conduct market research to identify relevant AI/ML tools, platforms, and vendors.

- Evaluate and select the best tools and vendors based on technical capabilities, cost-effectiveness, and alignment with business goals.

6. Team Management and Collaboration :

- Lead and mentor a team of Interns and support In-house/partner engineering teams

- Collaborate with cross-functional teams (product managers, designers, engineers) to deliver innovative solutions.

- Participate in data analysis, presentation, code review, business modeling, tech costing, partner collaboration, vendor app testing, evaluation, and reporting.

Required Skills :

- Strong foundation in AI/ML : Vertex AI, Deep learning, machine learning, neural networks, and statistical modeling.

- Proficiency in Python & Typescript : Experience with libraries like TensorFlow, PyTorch and Scikit-learn.

- Natural Language Processing : Expertise in NLP techniques, including text classification, sentiment analysis, and language generation.

- Data Engineering : Data pipelines, data cleaning, and feature engineering.

- MLOps : Model deployment, monitoring, and retraining.

- Experience working in Cloud Platforms such as AWS, Azure, or Google Cloud Platform with experience working on RESTfulAPIs, Microservices and Infra Set Up with Docker, Automated Builds, Linux

- Other General Engineering Tools & Apps : Version Control Tools : GIT, GITHUB, Design/ Workflows tool such as FIGMA/ WHimsical, Analytics : Google Analytics, Mixpanel/ Amplitude, Productivity : Notion/ Google

- Problem-solving and analytical skills : Ability to break down complex problems and develop effective solutions.

- Excellent communication and collaboration skills : Ability to work effectively with cross-functional teams.

Desired Skills :

- Experience with large language models (LLMs) : Lamda, BARD, Hugging Face, BERT, GPT-4, or similar.

- Computer Vision : Image and video analysis, object detection, and image generation.

- Reinforcement Learning : Developing AI agents that learn through interaction with an environment.

- Ethical AI : Understanding and addressing ethical considerations in AI development.

- Suppose you are passionate about AI and eager to contribute to various media technology products.