What are the responsibilities and job description for the Generative AI LLM Engineer Intern (AI/ML) position at Qubrid AI?
This is an unpaid internship opportunity . Work with Generative AI and LLM and learn how to code and work in a development environment to create AI products. This is not a theoretical AI research position and is also not suitable for general Ai, machine learning or deep learning experience. Focus is completely on Generative AI.
We are seeking intern Generative AI engineers to join our dynamic team. You will be responsible for training, tuning, deploying and optimizing LLM and SLM models and algorithms to address complex business problems. You will work closely with cross-functional teams to understand requirements, develop scalable solutions, and drive innovation in Generative AI technologies.
You'll work with our founders and US members plus off-shore cloud and AI team.
Responsibilities:
- Training, Finetuning, optimizing, implementing RAG etc on latest Generative AI models and developing algorithms that drive transformative solutions.
- Collaborate closely with cross-functional teams to identify business needs and translate them into AI-powered applications.
- Collect, preprocess, and analyze large datasets to uncover actionable insights and patterns.
- Explore emerging AI technologies and stay current with the latest advancements to continually enhance our AI offerings.
- Contribute to the end-to-end deployment of Generative AI solutions, ensuring scalability, performance, and reliability.
- Participate in code reviews and provide constructive feedback to maintain high-quality code standards.
- Champion best practices in AI ethics, data privacy, and security throughout the development process.
Requirements:
- Learn as a Generative AI Engineer, demonstrating proficiency in developing and deploying AI solutions.
- In-depth knowledge of Generative AI models such as Llama, Gemma etc
- Experience with machine learning algorithms, deep learning architectures, and relevant frameworks (e.g., TensorFlow, PyTorch) is a plus
- Proficiency in programming languages such as Python, along with experience in data manipulation and analysis.
- Strong grasp of mathematics and statistics concepts underpinning AI and machine learning.
- Familiarity with cloud platforms and tools for scalable AI model deployment.
- Effective communication skills in English, enabling seamless collaboration across global teams.
- Problem-solving mindset and a passion for staying at the forefront of AI innovation.
- A degree in Computer Science, Engineering, or a related field (or equivalent experience) will be advantageous.
Skills Required:
- Interest and academic experience in Generative AI field
- Experience with Image Processing technologies (e.g., Stabe Diffusion, OpenCV, Dlib, Pillow, NumPy, SIFT).
- Experience with Natural Language Processing (NLP/NLU) technologies and portals (e.g., HuggingFace, NLTK, Spacy, Flair)
- Familiar with Vertex AI
- Familar with Gemma, Mistral, Llama etc
- Proficiency in Deep learning frameworks (PyTorch, TensorRT, LangChain) is a plus
- Experience with person/scene understanding (pose, re-identification, etc.).
- Familiarity with Training of custom AI models like Detectors (YOLO), Classifiers, and Transformers.
- Technical knowledge in Latest Advancement in AI, especially in Vision (e.g., ViTs, CLIPs, and LLM models)
- Understanding of Docker and GIT
- Good understanding of optimizing data processing pipelines.
- Experience with successfully applying machine learning to solve a real-world problem.
