Description
Staff Data Scientist
Team: Data Science
Location: Palo Alto
Commitment: FTE
Workplace Type: onsite
Auxia is building the Agentic Customer Journey Orchestration Platform, redefining how enterprises activate, engage, and retain their customers through intelligent, adaptive AI systems. Backed by $23.5M in funding from top-tier investors — VMG Technology Partners, Stage 2 Capital, and MUFG Innovation Partners — we’re on a mission to make every enterprise truly intelligent.
Our founders, Sandeep Menon (ex-VP Marketing, Google) and Ravi Desu (ex-Global Engineering Lead, WhatsApp Payments @ Meta), are building Auxia with the same ambition and technical excellence that powered global platforms used by billions. Learn more about our vision here and here.
Today, Auxia powers 3B+ daily events, 6,500 queries per second, and 250M+ decisions per day, helping global enterprises like DOCOMO, Mercari, Atlassian and MUFG unlock the full potential of their first-party data.
Your Impact
As a Staff Data/ML Scientist, you’ll define and execute on the machine learning and AI roadmap, developing high-performance models and building agentic AI systems that drive real-time decisions across the platform.
You'll work across disciplines like recommender systems, LLMs, causal inference, and reinforcement learning, bringing ideas from research to production and helping shape the intelligence behind every Auxia user interaction.
What You’ll Do
- Design, implement, and refine ML models for personalization, ranking, and growth optimization
- Build and deploy autonomous, AI-driven agents capable of executing complex, multi-step tasks
- Lead research across recommender systems, transformers, RAG, and reinforcement learning
- Develop and improve offline evaluation metrics and model validation techniques
- Analyze large-scale customer data to extract insights and inform product strategies
- Collaborate with engineering, product, and business teams to translate research into impact
- Communicate findings internally and to key customers, shaping both product and strategy
- Stay current with the latest ML/AI research via literature reviews, conferences, and experimentation
What You Bring
- Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or related fields
- 7+ years of experience in training, deploying, and improving ML systems in production
- Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX
- Strong background in LLMs, RAG pipelines, and information retrieval systems
- Hands-on experience with recommender systems, feed ranking, and real-time user modeling
- Expertise in causal inference methods and experimental design
- Experience working with large-scale datasets in cloud environments (AWS, GCP, etc.)
- Ownership mindset—comfortable navigating ambiguity, taking initiative, and contributing beyond your immediate scope
Why Auxia
Impact - Be at the forefront of Agentic AI, driving the evolution of enterprise personalization — from manual segmentation to self-learning systems.
Influence - Work directly with Auxia’s founders and leadership team, alongside ex-Google, Meta, and Lyft engineers. Your insights will shape both our roadmap and the future of enterprise AI.
Work Environment
• 100% Onsite, Palo Alto (5 days/week) – because innovation thrives in collaboration.
• Fast-moving, research-driven environment where ideas turn into production within weeks.
• A team that believes in freedom with accountability — great minds solving hard problems, together.
Diversity, Equity & Inclusion - At Auxia, we are committed to building a workplace that celebrates diversity, fosters inclusion, and ensures equal opportunity. We welcome applicants from all backgrounds, regardless of race, gender, religion, age, sexual orientation, or disability.
⚡️ Ready to Join the Journey?Auxia is not just a company — it’s a movement to make every customer interaction intelligent, adaptive, and human. If you’re driven by deep technical challenges, global impact, and the chance to build with some of the sharpest minds from Google, Meta, and Lyft, this is your next big leap.
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