Principal Engineer - AI

US - Remote

About Worldly

Worldly is the world’s most comprehensive impact intelligence platform — delivering real data to businesses on impacts within their supply chain. Worldly is trusted by 40,000 global brands, retailers, and manufacturers to provide the single source of ESG intelligence they need to accelerate business and industry transformation.

Through strategic and meaningful customer relationships, Worldly provides key insights into supplier performance, product impact, trends analysis, and compliance. When a company wants to change how business is done, we enable that systemic shift.

Backed by a dedicated global team of individuals aligned by values, Worldly proudly operates as a public benefit corporation with backing from mission-aligned investors. Want to learn more? Read our story.

About The Role

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.

What You'll Do

• 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.

We'd Like to See

• 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.

It Helps If You Have

• 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.

What We Can Offer You

• 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

Life at Worldly

Our team is motivated to transform the way products are made. By helping our customers succeed in a new era of sustainable production, we can build technology that makes a difference on a planetary level.

Our team represents over 15 countries and brings unique experiences from technology to farming to the table. Surround yourself with kind, enthusiastic, and dedicated people who put collaboration and growth at the center of our shared goals.

Benefits and Perks

• 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.

Equity Statement

We believe it’s essential to reflect the diversity of those we strive to serve. True innovation happens when everyone has room at the table, including the tools, resources, and opportunity to excel. We’re dedicated to building a culturally and experientially diverse team that leads and works with empathy and respect.

Compensation Overview

Base Rate: $160k - $210k

Bonus: 10% annually

Equity: Equity Stock Option Program

*Final compensation details will be determined based on a wide variety of factors, including experience and location. These factors will be evaluated and considered by Worldly throughout the entire process.