Principal Engineer - AI

Worldly•Concord, CA

23d•Remote

About The Position

We are seeking a senior AI leader to help us expand our capabilities in predicting, analyzing, and mitigating environmental and social risk — across diverse, global, and often messy datasets. This role will guide how we apply cutting-edge AI/ML techniques to some of the world’s most pressing challenges, spanning pre-product R&D, core infrastructure design, and strategic product support. As the Principal AI Engineer, you will operate as both a Doer and a Leader — someone who is eager to dive into the data, prototype novel solutions, and push the boundaries of our platform’s intelligence layer, while also shaping strategic direction and mentoring the next generation of applied data scientists at Worldly. You’ll collaborate with engineering, product, and executive teams to design practical, scalable, and ethical AI solutions that deliver value across our core environmental and social modules. This is not a product management role — but you’ll be deeply involved in helping define what is possible, viable, and responsible when it comes to applying AI across the Worldly ecosystem.

Requirements

7+ years of experience in machine learning, data science, or applied AI, with a proven track record of owning end-to-end ML solutions in production.
Ability to balance hands-on technical work with strategic leadership and cross-functional collaboration.
Strong fluency in: Model development (e.g., PyTorch, TensorFlow, XGBoost)
Data science workflows (Python, Pandas, MLflow, Airflow, etc.)
ML and data infrastructure (feature stores, CI/CD for ML, reproducibility tools)
Experience mentoring, coaching, or leading other data scientists or technical contributors.
Comfort navigating ambiguity, especially in pre-product or exploratory problem spaces.

Nice To Haves

Background in climate tech, social impact, or supply chain analytics.
Familiarity with data governance frameworks (e.g., GDPR, CSRD, Chinese data localization).
Experience deploying AI systems in multi-regional or cloud-agnostic environments.
Contributions to open-source ML or data infrastructure projects.

Responsibilities

Design and lead AI/ML strategy for high-impact domains such as: Environmental risk modeling (climate, water, energy, etc.)
Social impact analytics (worker voice, audit parsing, wellbeing metrics)
Supply chain data fusion and predictive analytics
Retrieval-augmented generation (RAG) and generative AI for sustainability use cases
Get hands-on with data and models — prototyping solutions, validating hypotheses, and stress-testing assumptions through real experimentation.
Mentor and provide technical guidance to junior data scientists and analysts across the organization.
Partner with Engineering to design and validate the right tooling, pipelines, and infrastructure — from feature stores to model registries to evaluation frameworks.
Partner with Product to shape early-stage AI concepts into viable, explainable features — not as a PM, but as a technical architect and strategic guide.
Explore, evaluate, and adapt open-source models and frameworks to support our platform needs — including LLMs, embeddings, and multimodal systems.
Promote model quality, traceability, and ethical integrity, especially in regulated or high-stakes use cases across human and environmental systems.
Build secure models and data systems that respect the siloing of customer data in a multi-tenant environment.
Experience working with LLMs, RAG, or vector databases in enterprise or sustainability contexts.

Benefits

Comprehensive benefits offerings. 90% employee premium and 75% spouse/dependent premium covered by Worldly.
Company-sponsored 401 (k) with up to 4% match.
Incentive Stock Options
100% Parental Paid Leave
Unlimited PTO
13 company holidays
Earn a competitive salary and performance-based bonuses. Get healthcare, retirement matching, and equity for US employees.
Use the office stipend to get the supplies you need. Combat Zoom fatigue with Flex Fridays.
Flexible time off. Take the time you need to recharge. Our culture encourages team members to explore and rest to be their best selves.
We're remote, not lonely. Join the culture committee, coffee chats, or a variety of other interest groups.