AI Engineer [Freelancer]

Job Title: AI Engineer [Freelancer]

Location: Remote

Time Commitment: 3-4 hours on weekdays and 6-7 hours on weekends for the next 15 days

About: Tap Health

We are a healthcare technology company dedicated to simplifying medical access and improving healthcare outcomes. We empower individuals by enabling early illness detection through advanced symptom analysis, ensuring convenient and accessible healthcare for everyone.

Position Overview: AI Engineer/Intern

We are looking for a highly motivated and talented individuals to join our AI team and contribute to the development of our solution.

As an AI Engineer/Intern at Tap Health, you will be part of a dynamic team working on challenging and impactful projects at the intersection of artificial intelligence and health care. 

You will have the opportunity to apply your skills and knowledge in machine learning, deep learning, and other AI technologies to solve real-world problems.

While this is a freelance position, after the “Freelance” period, based on mutual agreement would be very keen to extend you a full-time position.

Responsibilities

• Develop and implement NLP algorithms and models to address specific business challenges.
• Fine-tune Large Language Model(LLM) model using Indian language data to address specific business challenges
• Collaborate with cross-functional teams to understand project requirements and deliver AI solutions.
• Conduct research and stay up-to-date with the latest advancements in AI and Large Language Model(LLM).
• Preprocess and analyze large datasets to extract meaningful insights.
• Optimize and fine-tune existing NLP and LLM models for improved performance.
• Work closely with software engineers to integrate AI solutions into existing systems.

Qualifications

• Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Strong programming skills in languages such as Python.
• Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch).
• Experience with data preprocessing, feature engineering, and model evaluation.
• Familiarity with deep learning techniques and neural network architectures.
• Knowledge of natural language processing, computer vision, Large Language Models, ML, DL, etc.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.