About Trademo :

At Trademo, we are transforming global trade and supply chains by leveraging cutting-edge AI technology to provide businesses with unparalleled visibility, compliance, and intelligence solutions.

Our AI-driven platform simplifies the complexities of international trade, helping companies mitigate risks, enhance efficiency, and make data-driven decisions with confidence.

Our AI-Enhanced Solutions :

- Trademo Intel AI-powered trade intelligence to uncover market trends and competitive insights.

- Trademo Sanctions Screener AI-driven compliance with 650+ global sanctions and PEP lists.

- Trademo Global Trade Compliance Real-time regulatory and tariff data for 140+ countries, with AI workflows for HS/ECN classification, controls determination, and licensing.

- Trademo Map AI-powered global supply chain mapping and screening, detecting risks like Forced Labor (UFLPA) and sanctions in deep-tier networks.

- Trademo TradeScreen AI-powered trade transaction digitization, financial crime screening and compliance platform.

Trademo collects and integrates diverse open-source data points to create our AI-driven knowledge graph, TrademoKG.

These data points include Customs Declarations, Shipping Data, Satellite Data, AIS Data, Vessels, Web Footprints, Global Tariffs & Duties, FTAs, Import/Export Controls, Export Licenses, Key Personnel & Ownership, Company Financials, and Company Legal information.

By analyzing trade data from 200+ countries, Trademo uses AI to provide deep insights, ensuring visibility and compliance across global supply chains.

Founded by Shalabh Singhal, who is a third-time tech entrepreneur and an alumni of IIT BHU, CFA Institute USA, and Stanford GSB SEED.

Our Trademo is backed by a remarkable team of leaders and entrepreneurs like Amit Singhal (Former Head of Search at Google), Sridhar Ramaswamy (CEO, Snowflake), Neeraj Arora (MD, General Catalyst & Former CBO, Whatsapp Group.

Key Responsibilities :

- Build and productionize AI-driven features, especially those powered by LLMs and NLP techniques.

- Lead hands-on experimentation with GenAI use cases, prompt engineering, retrieval systems, and fine-tuning.

- Design, develop, and maintain scalable ETL pipelines and data workflows using modern data stack technologies (Spark, Kafka, Airflow, Snowflake, etc.

- Own architecture decisions for model training, evaluation, and deployment.

- Collaborate with domain experts and product teams to create proprietary labeled datasets.

- Lead and mentor a growing team of data engineers and AI/ML engineers.

- Establish engineering best practices, QA, monitoring, and observability across data systems.

- Drive initiatives to automate, optimize, and intelligently scale our internal and external data operations.

Desired Profile :

- Bachelor's or Masters degree in Computer Science, Engineering, Data Science, or a related field.

- 8+ years of experience in data engineering and applied machine learning.

- 3+ years in a team leadership or technical lead role.

- Deep, hands-on experience with building data pipelines, model deployment, and cloud-based infrastructure.

- Strong knowledge of LLM ecosystem (OpenAI, HuggingFace, vector DBs, retrieval frameworks, etc.

- Experience building GenAI use cases in production (e.

, retrieval-augmented generation classification, summarization).

- Strong coding skills (Python preferred), with a bias for action and clean, scalable architecture.

- Excellent problem-solving and communication skills; ability to work across function.