Machine Learning Engineer (NLP, Search & Recommendation)

About Climatiq

We are a fast-growing climate tech startup on a mission to drive climate action through data and insight. Our team consists of entrepreneurs, technologists, and scientists who have come from backgrounds such as Google, MIT, and other leading companies and academic institutions. Together, we are building a tech platform that empowers organizations to take action in tackling the climate crisis. Our powerful carbon calculation engine helps businesses embed emission metrics into any software they already use to accurately calculate and continuously monitor their carbon footprint and drive better decisions.

Our platform is used by tens of thousands of sustainability leaders worldwide, and we are proud to be backed by renowned international VCs and investors in the climate-tech and software sector. We are also a certified B Corp, highlighting our commitment to balancing purpose and profit. As a remote-first company, our team is spread out across Berlin and other parts of Europe, with a strong focus on collaboration and innovation.

This is an exciting time to join Climatiq. Be part of a real, technology-driven endeavor from the beginning. Work with an amazing team and help build something meaningful together with our community.

Job Description

We are looking for an experienced Machine Learning Engineer with a focus on Search, Recommendation Engines, Information Retrieval, and Text Classification. Reporting to the CTO, you’ll collaborate with a team of developers, scientists, and climate experts to improve our critical AI-based features like Autopilot, which are at the heart of our mission to tackle the climate crisis. We are looking for self-driven engineers who bring fresh ideas and are able to develop a product autonomously in a collaborative environment.

Responsibilities:

1. Design, develop, and maintain critical features using Machine Learning Models, NLP, Information Retrieval, and other relevant methodologies, powering the infrastructure for carbon intelligence globally and across industries for all business activities and products.
2. Play a key role in delivering key data and insights into leading software platforms used by the largest enterprises across the world, powering billions of calculations in critical environments via our API, enhancing carbon visibility and climate action for organizations.
3. Train, optimize, evaluate, and experiment with various models (e.g., transformers, classifiers, encoders, LLMs) to improve key product metrics for our search and recommendation engine on top of GHG emissions data.
4. Maintain and improve our data pipelines, ensuring data readiness for modeling.
5. Deploy and maintain models in production using technologies like AWS SageMaker, Flask, and Pydantic.

Required Qualifications:

1. 5+ years of experience in Machine Learning Engineering, in the domains of Search, Classification, and Information Retrieval.
2. 3+ years of experience in Python, building data pipelines and REST APIs.
3. Self-driven and comfortable working autonomously, with excellent problem-solving skills.
4. Strong written and verbal communication skills, with experience collaborating across remote teams, ensuring clear, effective, and aligned outcomes.

Preferred Qualifications:

1. Experience with managing AWS infrastructure is a plus.
2. Prior experience with PostgreSQL is a plus, especially in a production environment.
3. Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.

Additional Information:

1. Location: Berlin or Remote within +/- 2 hours of CET timezone
2. Starting date: As soon as possible
3. Hours: Full-time, flexible working hours
4. Compensation: Competitive salary and benefits, including employee stock options, learning and development stipend, regular team offsites, and more.

As a certified B Corp, Climatiq is an equal-opportunity employer and we welcome and encourage candidates from all backgrounds and experiences to apply for roles on our team. Send us your CV and a short cover letter, highlighting your skills and experience, relevant for the advertised role.

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