Who are we, you ask?
Interviews can be hard, especially at top tech companies like Google, Facebook, and Netflix. Many candidates fall short simply because they aren’t adequately pepared. That’s where we come in. Our acclaimed courses specialize in interview preparation and transitioning into high-demand tech fields such as AI, ML, and Data Science. At Interview Kickstart, current and former hiring managers have guided over 17,000 tech professionals through transformative career journeys, ensuring their success in landing coveted positions. Think of us as “the everything store” for career transitions and interview skill development.
How do we do that, you ask?
We have a structured approach to interview success, which includes:
What’s more exciting is - we are completely remote, and we are hiring the best people we can find regardless of geography.
We have recently launched multiple GenAI courses to help ML and non-ML working professionals explore the world of Generative AI. We are looking for Generative AI experts - part-time Instructors. This role will provide opportunities to network with other experts, understand learner issues and contribute to the GenAI community.
Requirements:
Technical Expertise in at least one of the following topics:
1. Deep Learning Fundamentals: ● understanding of neural networks, including feedforward, recurrent (RNN), and convolutional neural networks (CNN). ● Knowledge of mathematical foundations for Generative AI
2. Generative AI Techniques: ● Experience with transformer architectures, including encoder-decoder models and the attention mechanism. ● Proficiency in evaluating Generative AI models using appropriate metrics. ● Awareness of ethical considerations in Generative AI
3. Large Language Models (LLMs):
● Understanding of LLM concepts, including pre-training (MLM, NSP) and self-supervision techniques.
● Knowledge of scaling laws and their implications on model performance.
● Familiarity with deploying and optimizing LLMs in production environments.
4. Application Development with LLMs
● Retrieval-Augmented Generation (RAG)
● LangChain as a toolkit for LLM applications
● Pretraining and fine-tuning LLMs, Instruction Tuning, Learning from Preferences
● Building a RAG application or a custom AI solution with OpenAI APIs
5. Diffusion Models:
● Expertise in Denoising Diffusion Probabilistic Models (DDPM) and stable diffusion.
● Experience with fine-tuning diffusion models and understanding latent diffusion techniques.
● Knowledge of visual transformers and their applications.
6. Multimodal Models:
● Understanding of integrating and processing multiple data types (text, images, audio) in AI models.
● Familiarity with multimodal learning processes, including representation, alignment, and reasoning.
7. Reinforcement Learning (RL):
● Proficiency in RL fundamentals, including the multi-arm bandit problem and Deep Q-learning.
● Experience with applying RLHF (Reinforcement Learning from Human Feedback) on LLMs.
8. Experience with cloud platforms like AWS and AI development and deployment tools.
9. Generative AI for Images and Audio:
● Knowledge of text-to-speech synthesis techniques (e.g., Tacotron, WaveNet).
● Experience in creating and fine-tuning models for new music and sound generation using GANs.
● Understanding of voice models and integration of voice with LLM
10. Specialized Domain-Specific Roles
● Applied GenAI: PM Pathway - At least 5+ years of experience managing AI Products as a Product Manager. Hiring experience preferred.
● Applied GenAI: SDE Pathway - At least 7+ years of experience as an SDE, out of which at least 3+ years of experience in building AI products using Generative AI Technologies.
● Applied GenAI: TPM Pathway - At least 5+ years of experience managing AI Products as a Technical Product / Program Manager. Hiring experience preferred.
● Applied GenAI: EM Pathway - At least 5+ years of experience managing Engineering teams working with the latest Generative AI technologies. Hiring experience preferred.
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