About Intervue.io:
Intervue.io is revolutionizing the technical hiring landscape by providing an all-in-one platform that streamlines the interview process. Our mission is to empower companies to hire better and faster through standardized, scalable, and efficient technical interviews.
With a growing presence in the India, US, and MENA regions, and a dynamic team based in HSR Layout, Bangalore, we're poised for our next phase of growth. As a seed-stage startup that has grown 4X year-over-year, we're looking for ambitious talent to join our journey.
Designation: AI Founding Engineer
Location: Bangalore, Onsite
Key Responsibilities:
- Design, Train, and Fine-tune Models: Design, train, and fine-tune large-scale language models (LLMs) for specific use cases.
- Optimize Model Performance: Enhance model speed, accuracy, and cost-efficiency.
- Model Inference Pipelines: Implement and improve model inference pipelines for deployment.
- Research & Experimentation: Continuously research and experiment with state-of-the-art NLP techniques and architectures.
- APIs & Integration: Develop APIs and interfaces for integrating LLMs into products and applications.
- Collaboration: Work with cross-functional teams (product managers, data scientists, software engineers) to align AI capabilities with business objectives.
- Responsible AI Practices: Ensure ethical AI usage, mitigate biases, and adhere to responsible AI guidelines.
- Monitoring & Evaluation: Monitor model performance and continuously improve its robustness and efficiency.
- Benchmarking: Assess LLMs for hallucination rates, factual consistency, and response quality.
- Evaluation Frameworks: Develop and implement evaluation frameworks using custom metrics to measure model performance.
Required Skills & Qualifications:
- Experience: Minimum of 5 years in the data science domain, ideally in a product-based company.
- LLM Expertise: Proven experience working with large language models like LLAMA, ChatGPT, Mistral, etc.
- RAG & Fine-tuning: Familiarity with retrieval-augmented generation (RAG) and fine-tuning large language models.
- Agentic Framework: Experience with agentic frameworks like Langchain, Langgraph, etc.
- Data Pipeline Knowledge: Strong understanding of data pipeline management.
- Technical Skills: Proficiency in Python and deep learning frameworks such as TensorFlow or PyTorch.
- Optimization & Deployment: Experience with model training, fine-tuning, optimization techniques, and deployment (Containerization).
Additional Skills:
- Prompt engineering
- Parameter-efficient fine-tuning (LoRA, PEFT)
- Strong problem-solving and communication skills
- Ability to work in a fast-paced environment
Bonus Skills:
- Frontend : React(SSR), Redux, Typescript
- Backend : Node, Express, Redis, Postgres
- Aws services like s3, lambda, cloud front, ec2, Eks
- knowledge in Infra(AWS, Docker, Kubernetes), Release Engineering, CI/CD, other tools and frameworks
