Machine Learning Engineer

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Overview

At Unravel Carbon, we're on a mission to accelerate the world's transition to a zero-carbon economy. We're a team of entrepreneurs, engineers, and climate experts who believe that data and AI are the keys to unlocking a sustainable future. Our Sustainability AI agents platform helps companies across the globe to measure, reduce, and report their carbon emissions with unprecedented accuracy and efficiency. We're backed by top-tier investors like Sequoia and Y Combinator, and we're growing fast.

What You Will Work On

• Build AI agents for sustainability professionals that automate emissions calculations, extract insights from emissions inventory, generate sustainability reports, and streamline other key sustainability workflows.
• Develop LLM-powered systems that process and understand sustainability data from various sources like invoices, utility bills, and supply chain documents.
• Build agentic workflows that combine language models with structured data processing and domain-specific reasoning capabilities.
• Continuously improve our multi-ML model (semantic search and text classification) carbon engine that calculates carbon emissions, using millions of lines of transactional data and our proprietary data set of carbon emission factors.
• Design and build scalable, modular ML services on AWS infrastructure that serve both traditional ML models (transformer-based models like ModernBERT, T5) and LLM-based systems in production.
• Implement evaluation frameworks and quality controls for LLM-based systems to ensure reliable performance in production.
• Lead our efforts to build AI-powered systems that leverage our various data sets to automatically identify and recommend decarbonization solutions for our customers.

About You

• You have 1-3 years of experience in Machine Learning, Generative AI or are an upcoming new graduate with extensive relevant internships.
• You have strong experience in Python, SQL and are comfortable with modern ML frameworks like transformers, LangChain, or similar libraries.
• You are familiar with LLMs, prompt engineering, and have worked with LLM APIs or built RAG systems.
• You have shipped NLP/ML solutions to production and can demonstrate the impact of your work.
• You are able to own the entire lifecycle of a Machine Learning project. You don't need to be an expert on every aspect of it, but you must be a quick learner to pick things up and go deep when needed.
• You have an understanding of system design and can build scalable ML services.
• You like to think through product problems and enjoy working cross-functionally.
• You use solid engineering practices, write maintainable code, and care about code quality.
• You are proficient with AI-based coding tools and use them effectively in your workflow.
• You thrive in a fast-paced environment and can adapt quickly to changing priorities.
• You enjoy mentoring others where you can.

Bonus Points If

• You have experience with LLM evaluation, guardrails, or agent frameworks.
• You have worked with vector databases and embedding systems.
• You have domain knowledge in sustainability, carbon accounting, or climate tech.
• You have a Master or PhD degree in Computer Science, Applied Computing, Computational Linguistics, Machine Learning or a related field.

What Youll Gain

• Opportunity to shape product direction and team culture at a fast-growing climate tech startup backed by top-tier investors.
• Work directly with founders and senior leadership on products that have material impact on fighting climate change.
• Gain deep expertise in applying cutting-edge AI techniques to solve critical sustainability challenges.
• Experience building production AI systems at scale while contributing to the world's transition to a zero-carbon economy.

Seniority level

• Entry level

Employment type

• Full-time

Job function

• Engineering and Information Technology

Industries

• Climate Data and Analytics