Team Size: 3 core engineers
Total Funding: $3M Pre-seed
Visa Sponsorship: Available for qualified candidates
About the Opportunity
An emerging startup at the intersection of AI and video intelligence is seeking a passionate and highly skilled AI/ML engineer to join as a founding team member. This role offers the chance to work alongside experienced engineers, shape the core product, and receive significant early equity as the company grows through its next major phase.

What You’ll Do

• Architect, build, and deploy advanced AI/ML systems for video understanding, content search, tagging, and agentic workflows.
• Develop and optimize multi-model pipelines (e.g., LLMs, VLMs), evaluation frameworks, and robust prompt workflows to ensure accuracy, latency, reliability, and cost efficiency at scale.
• Work with vector databases, embeddings, and Retrieval-Augmented Generation (RAG) infrastructures to handle vast video corpora.
• Productionize and scale systems on modern cloud infrastructure.
• Continuously improve workflows based on feedback and evolving customer requirements.
• Collaborate tightly with the core engineering team on product and technical strategy.

Requirements

WORK EXPERIENCE

• Experience at an early-stage startup, including scaling a technical product.
• Demonstrated progression and growth in past roles.
• Preferred: Exposure to self-driving, computer vision, or similar high-throughput domain pipelines.

TECHNICAL SKILLS

• Hands-on experience with LLM/VLM APIs such as OpenAI, Anthropic, Gemini, Llama, or SigLIP.
• Expertise in video intelligence, advanced search, or recommendation systems.
• Strong understanding of embeddings, retrieval techniques, and RAG architectures.
• Experience with prompt optimization, model fine-tuning, and evaluation.
• Highly proficient in Python and the modern ML stack (e.g., PyTorch, Hugging Face).

EDUCATION

• Preferably hold a degree from a top global university (e.g., IIT, Stanford) or equivalent proven excellence.

• Architect, build, and deploy advanced AI/ML systems for video understanding, content search, tagging, and agentic workflows.
• Develop and optimize multi-model pipelines (e.g., LLMs, VLMs), evaluation frameworks, and robust prompt workflows to ensure accuracy, latency, reliability, and cost efficiency at scale.
• Work with vector databases, embeddings, and Retrieval-Augmented Generation (RAG) infrastructures to handle vast video corpora.
• Productionize and scale systems on modern cloud infrastructure.
• Continuously improve workflows based on feedback and evolving customer requirements.
• Collaborate tightly with the core engineering team on product and technical strategy