Highlights
AI agent development, hands-on ML experimentation, transition to full-time role
Description
Job Summary
pWe are seeking an AI Research Engineer Intern to join our team and contribute to the development of cutting-edge AI solutions for healthcare enterprises. This role involves hands-on experience with AI agent development, ML experimentation, and deployment of models into production systems.
Responsibilities
- Building and debugging multi-step AI agents
- Designing and running ML experiments from hypothesis to evaluation
- Implementing model pipelines including data preprocessing and inference
- Evaluating model outputs for accuracy and fidelity
- Reading research papers and implementing new ideas quickly
Required Skills
- Proficient in Python programming
- Data structures and algorithms knowledge
- Martin experimentation experience
- Familiarity with PyTorch or TensorFlow
- Experience with LLM APIs or agent frameworks
Required Skills Explained
- Strong programming ability in Python: Proficiency in writing clean, efficient code that adheres to best practices.
- Strong understanding of data structures, algorithms, and backend engineering fundamentals: Demonstrated knowledge of core concepts such as data manipulation, algorithmic thinking, and system architecture.
- Hands-on experience building ML or deep learning models: Practical experience in developing machine learning models from scratch or fine-tuning existing ones for specific use cases.
- Familiarity with PyTorch, Pandas, TensorFlow, Scikit-learn, or similar tooling: Ability to leverage popular libraries and frameworks to implement and optimize solutions efficiently.
- Experience working with LLM APIs, embeddings, RAG pipelines, or agent frameworks: Knowledge of advanced AI technologies such as language models, embeddings, retrieval-augmented generation (RAG) systems, and multi-agent architectures.
- Experience building AI agents, automation systems, or ML pipelines: Hands-on experience in creating AI-driven tools and processes that automate complex workflows.
- Understanding of neural networks, training workflows, inference, and evaluation concepts: In-depth knowledge of the inner workings of neural networks and their practical applications.
- Familiarity with APIs, async programming, or backend system integration: Experience in designing scalable systems that interact with various services and data sources.
- Comfortable reading research papers and implementing ideas into working systems: Ability to quickly understand and translate academic research into tangible solutions.
Who is this for
pThis role is ideal for recent graduates in Computer Science, AI, or Machine Learning who are passionate about building systems and experimenting with AI models. Candidates should have a strong track record of independent learning and be self-driven.
Why This Job is a Good Opportunity
ulliYou'll have the chance to work directly with a founding engineering team, contributing to groundbreaking projects from day one.liThe opportunity to develop real-world AI applications that impact healthcare enterprises on a global scale.liHigh visibility and rapid learning curve due to direct involvement in high-impact projects.liA pathway to full-time employment for top performers, ensuring long-term career growth within the company.liAn environment that values hard work and continuous improvement, pushing you to excel both technically and personally.
Interview Preparation Tips
- Review core concepts in Python programming and data structures/algorithms to ensure a strong foundation.
- Prepare examples of your AI/ML projects, especially those involving deep learning or agent systems, for potential discussion during the interview.
- Be ready to discuss your experience with LLM APIs, embeddings, RAG pipelines, and other advanced AI technologies.
- Understand common interview questions related to model training workflows, inference processes, and evaluation techniques.
- Bring a list of research papers that you have read and implemented to demonstrate your ability to translate theoretical knowledge into practical applications.
Career Growth in This Role
pThis role offers significant opportunities for career advancement. As an AI Research Engineer Intern, you will be at the forefront of developing innovative solutions that drive the company's mission forward. Your contributions can directly impact real-world applications and set a path for future leadership positions within the organization. The internship-to-hire pathway provides a clear progression to full-time roles, ensuring continuous growth and development in your career as an AI engineer.
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Skills
Frequently Asked Questions
Is this a remote position?This is an in-office internship only.
What kind of projects can I expect to work on?You will work on building and debugging AI agents, designing ML experiments, and implementing model pipelines for production systems.
How long is the internship duration?The internship lasts 3-6 months with a pathway to full-time employment.
