
Chief AI Architect
3 days ago
About Our Company
We are a fast-growing enterprise B2B SaaS startup founded by ex-Amazon ad-tech experts. Our mission is to build a future-proof Retail Media Operating System, helping retailers boost profitability.
Job Summary
We seek a Senior Data Scientist to design, build, and scale AI-powered solutions for retail media and ad-tech. This role combines technical leadership, applied research, and business impact, requiring expertise in machine learning, deep learning, natural language processing, and large language models.
Key Responsibilities
- Translate complex business problems into advanced statistical and ML frameworks.
- Develop scalable ML and DL solutions with an emphasis on LLMs and Generative AI.
- Build and optimize training, fine-tuning, evaluation, and deployment pipelines for LLMs.
- Apply Responsible AI principles to ensure fairness, explainability, and bias mitigation.
- Lead applied research and incorporate cutting-edge GenAI methods into production.
- Build scalable data pipelines and end-to-end ML systems on cloud platforms.
- Provide technical leadership to data scientists, analysts, and engineers.
- Mentor junior talent, establish best practices, and influence the data science roadmap.
- Partner with cross-functional teams to integrate AI solutions into customer-facing platforms.
Required Skills and Qualifications
- Master's or PhD in Computer Science, Statistics, Data Science, or related fields.
- 8–12 years of applied data science/ML experience, with domain exposure to e-commerce, advertising, or retail.
- 3–4 years of hands-on expertise in LLMs, Generative AI, and NLP.
- 2+ years of leadership experience guiding projects and teams.
- Strong proficiency in Python, SQL, PyTorch/TensorFlow, and cloud ML platforms.
- Experience with MLOps frameworks.
- Solid statistical foundation.
- Strong data engineering skills for ETL and large-scale dataset processing.
Nice to Have
- Experience with ad-tech, ad-serving systems, or retail media platforms.
- Applied research contributions.
- Exposure to multimodal AI and personalization systems.
- Hands-on experience with LangChain, Hugging Face, RAG, LoRA, and fine-tuning of LLMs.
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