Auf einen Blick
- Aufgaben: Design and develop cutting-edge ML applications to combat climate change.
- Arbeitgeber: Join Climatiq, a fast-growing climate tech startup on a mission for climate action.
- Mitarbeitervorteile: Enjoy remote work, competitive salary, stock options, and learning stipends.
- Warum dieser Job: Be part of a meaningful tech-driven endeavor with a passionate team.
- Gewünschte Qualifikationen: 5+ years in Machine Learning; strong Python skills; experience in data pipelines.
- Andere Informationen: Flexible hours, remote work within +/- 2 hours of CET timezone.
Das voraussichtliche Gehalt liegt zwischen 43200 - 84000 € pro Jahr.
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 Data Engineering, Information Retrieval, and Text Classification. Reporting to the CTO and working across our Engineering, Science, and Data teams, you are passionate about building bleeding-edge ML applications 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:
- Design, develop, and maintain features using Machine Learning Models, NLP, Information Retrieval and other relevant methodologies that power the infrastructure for carbon intelligence globally and across industries for all business activities and products.
- Play a key role 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.
- Source, process, and standardize data from multiple sources, ensuring data quality and readiness for modeling.
- Train, optimize, and evaluate various models (e.g., classifiers, encoders, LLMs) to enhance accuracy and effectiveness.
- Deploy and maintain models on AWS, particularly with SageMaker, while managing production pipelines and conducting necessary testing, monitoring model performance, troubleshooting issues, and implementing enhancements based on feedback and analysis.
- Develop and explore innovative methods for modeling multilingual, semi-structured, and hierarchical data, with a focus on building a search engine on top of GHG data.
Required Qualifications:
- 5+ years of experience in Machine Learning Engineering, Architecture, Modeling, Data Pipelines, Data Extraction and Augmentation, Classification and Processing.
- 3+ years of experience in Python, building data pipelines and REST APIs.
- Demonstrated experience in designing and implementing search and classification systems within the information retrieval domain, with a focus on optimizing relevance, accuracy, and scalability across complex datasets.
- Self-driven and comfortable working autonomously, with excellent problem-solving skills.
- Strong written and verbal communication skills, with experience collaborating across remote teams, ensuring clear, effective, and aligned outcomes.
Preferred Qualifications:
- Experience with managing AWS infrastructure is a plus.
- Prior experience with PostgreSQL is a plus, especially in a production environment.
- Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
Additional Information
Location: Berlin or Remote within +/- 2 hours of CET timezone
Starting date: As soon as possible
Hours: Full-time, flexible working hours
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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Machine Learning Engineer (NLP) – Climate Tech Arbeitgeber: NLP PEOPLE
Kontaktperson:
NLP PEOPLE HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Machine Learning Engineer (NLP) – Climate Tech
✨Tip Number 1
Familiarize yourself with the latest advancements in Machine Learning, especially in NLP and Information Retrieval. Being able to discuss recent trends or breakthroughs during your interview can demonstrate your passion and expertise in the field.
✨Tip Number 2
Showcase your experience with AWS, particularly SageMaker, as this is crucial for the role. If you have any personal projects or contributions that involved deploying models on AWS, be ready to discuss them.
✨Tip Number 3
Prepare to talk about your experience with data pipelines and REST APIs in Python. Be specific about the challenges you faced and how you overcame them, as this will highlight your problem-solving skills.
✨Tip Number 4
Since Climatiq values collaboration in a remote environment, think of examples where you've successfully worked with distributed teams. Highlight your communication strategies and how you ensured alignment across different time zones.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Machine Learning Engineer (NLP) – Climate Tech
Tipps für deine Bewerbung 🫡
Tailor Your CV: Make sure to customize your CV to highlight your experience in Machine Learning Engineering, particularly focusing on Data Engineering, Information Retrieval, and Text Classification. Use specific examples that demonstrate your skills and achievements relevant to the role.
Craft a Compelling Cover Letter: Write a short cover letter that not only summarizes your skills and experience but also expresses your passion for climate tech and how you can contribute to Climatiq's mission. Mention any relevant projects or experiences that align with their goals.
Showcase Technical Skills: In your application, emphasize your technical skills, especially in Python, AWS, and building data pipelines. Provide concrete examples of how you've successfully implemented these skills in previous roles.
Highlight Collaboration Experience: Since Climatiq values collaboration across remote teams, include examples of how you've effectively communicated and worked with others in a remote setting. This will demonstrate your ability to thrive in their work environment.
Wie du dich auf ein Vorstellungsgespräch bei NLP PEOPLE vorbereitest
✨Show Your Passion for Climate Tech
Make sure to express your enthusiasm for climate action and how your skills in machine learning can contribute to this mission. Share any relevant projects or experiences that demonstrate your commitment to sustainability.
✨Highlight Your Technical Expertise
Be prepared to discuss your experience with machine learning models, NLP, and data engineering. Provide specific examples of projects where you designed and implemented search and classification systems, focusing on the challenges you faced and how you overcame them.
✨Demonstrate Collaboration Skills
Since Climatiq values collaboration across remote teams, share examples of how you've successfully worked with others in a distributed environment. Highlight your communication skills and how you ensure alignment and effective outcomes in team settings.
✨Prepare for Technical Questions
Expect technical questions related to AWS, Python, and data pipelines. Brush up on your knowledge of deploying models on AWS, particularly with SageMaker, and be ready to discuss your approach to optimizing model performance and troubleshooting issues.