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Machine Learning Engineer at LogSpend (Full-time)



Software Engineering
Posted on Friday, May 3, 2024

Machine Learning Engineer at LogSpend (Full-time)

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1. Who we are

🚢 LogSpend is building the self-serve analytics platform for AI-native products. We recognize that building LLM products is hard and so we help product teams get an in-depth view of how their users are interacting with their products so they can build the best AI-powered user experiences.
Location: Barcelona, Spain ☀️ Job type: Full-time
👨‍👨‍👧‍👦 The next frontier of user experiences will be AI-powered and our mission is to accelerate this transition into an AI-first world by enabling companies create more value for their customers and end users through delightful AI-powered experiences.
🎯 LogSpend equips product teams with the super powers to go beyond tracking explicit user actions to gleaning insights from unstructured user interaction and navigation data. We do this by simplifying complex data collection and reconciliation from multiple sources to ensure high-quality data at the source, automating insight extraction at scale and providing full flexibility on how these insights are consumed and acted upon by product teams.
We’ve processed over 100M user interactions to date and serve several data-driven and AI companies. If you’re excited about the potential to redefine what the future of data-driven organizations should look like in an AI-first world, then you just might have found your band!
🎶 We are a VC-backed company built by two founders who spent the last 6 years at Spotify shipping personalized listening experiences to millions of Spotify users globally.

2. About the role

We are currently seeking an experienced Machine Learning Engineer to join our growing team. As a Founding Engineer on the team, you will be responsible for building a robust, scalable and cost-efficient machine learning infrastructure for extracting valuable insights from heterogenous sources of unstructured and structured data. You will experiment with different types of models and model architectures to come up with novel solutions to enhance our platform’s capabilities.

Key Responsibilities

Leverage advanced NLP techniques to extract highly relevant information from unstructured data and user conversations
Fine-tune models, such as LLMs, for different domains like travel, e-commerce, customer support, learning, etc.
Build and maintain a robust and scalable machine learning infrastructure to serve millions of inferences at lightning speed
Ensure the metrics and insights provided by our platform are of high quality, accurate, and trustworthy


Strong background in NLP and experience working with LLMs
Proficiency in fine-tuning models for various domains
Experience building data pipelines and high-quality data products
Familiarity with MLOps best practices
Experience in managing machine learning infrastructure at scale in a production environment
Ability to work collaboratively with cross-functional teams to deliver high-quality insights

Additional Requirements

Ability to work across the stack and pick up new tools/technologies
Strong problem-solving skills and ability to work in a fast-paced environment
Excellent communication and interpersonal skills

3. Why you definitely want to work with us

🚀 Asides from being part of an exciting mission and building things from scratch, you’ll be part of a small fun and ambitious team that loves moving fast and trying things out.
👨‍👨‍👧‍👦 You’ll be doing one of the most impactful works of your career, making people’s lives better through AI.
🥳 You will work hard, but we will celebrate the small and big wins together.
🎉 We will organize company offsites several times a year to work and play together.
💰 And of course, you will get a competitive salary, significant equity ownership, health insurance and professional development opportunities!

4. Where to apply

Send your application at careers@logspend.com if you think you could be a great fit!
Please note: we are not interested in receiving assistance from recruitment or staffing agencies. Thank you for your understanding.