[Outgoing] Applied ML Engineer

Permanent contract
A few days at home
Salary: Not specified
Starting date: September 28, 2025

Imagination Machine
Imagination Machine

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The position

Job description

Are you an entrepreneurial engineer with experience applying AI in a fast-paced environment? Are you excited to apply those skills on something with positive benefits to society: using technology to get people off their screens? Outgoing is looking for a hands-on, applied AI engineer, fluent in implementing and experimenting in the fast-evolving open-source LLM space, ready to operate at startup velocity, on a cool, consumer-facing product that’s good for the world.

What You’ll Do

As our Applied ML Engineer, you’ll lead designing, developing, and deploying the core AI systems for Outgoing’s personalized activity recommendations engine. Key opportunities and responsibilities include:

  • Owning End-to-End Development of Algorithms Platform: We’re looking for someone independent, who can take full ownership of key features from concept to deployment, developing robust systems in a fast-paced environment. We value experimentation over perfection — this isn’t a theoretical role — and are trying to quickly deliver value to our users.

  • Implementing & Optimizing LLM-Powered Features: Integrate and fine-tune open-weight LLMs for natural language understanding, classification, content generation, and conversational interfaces.

  • Developing Advanced Ranking & Recommendation Algorithms: We’ve got some innovative approaches to the typical recommender system cold-start problem, so you’ll be helping supercharge classical ranking and information retrieval algorithms.

  • Driving Technical Architecture & Tooling Decisions: We’re an early-stage startup so there’s loads of opportunity for contributing and owning strategic technical decisions like system architecture, technology stack, and platform evolution.


Preferred experience

  • 3+ years of hands-on engineering experience applying AI, ML, and algorithms to complex, user-facing products

  • Proven hands-on experience deploying custom LLMs and SLMs in production environments, ideally including fine-tuning and quantizing models such as Gemma, Llama, and Qwen

  • Familiarity with ranking algorithms and recommendation systems, with experience in their design, implementation, and optimization, in fields such as social media, advertising, or consumer applications

  • Experienced with Python (including Pydantic) and ML frameworks, with bonus points for familiarity with FastAPI, Google Cloud Platform, and vector & graph databases

  • Bonus: This role is primarily working in our Python layer, but bonus points for experience with Flutter, Node.js, and/or Rust

Our Culture

We’re a team that values collaboration, proactive problem solving, and strong empathy. You’ll thrive here if you

  • Are a proactive builder: You don’t wait for perfect specifications: you prototype, iterate, and drive solutions forward

  • Embrace learning & teaching: This moment in technology is moving incredibly fast; our team wins when we stay on top of the latest trends and share learnings with each other

  • Communicate with clarity: Particularly as a remote team, articulating complex technical and product concepts simply is paramount. We favor async design discussions when possible.

  • Are obsessed with our users: Building a consumer product is about putting our users first above technology; we’re using tech to build something that truly delights

Work Setup

We are a remote-first team operating in the European time zone (HQ in Paris) and communicating in English. This is a full-time role with competitive salary, benefits and equity.

Whom You’ll Work With

We’re seasoned entrepreneurs and engineers from some of the largest consumer technology companies, so you’ll have a chance to collaborate and learn with an experienced, technically-deep, mission-driven team, including:

Mark, Rob, Juan, JF, Ludo, Matt, Naveen, and more.

Does the idea of building AI that brings people together excite you? We’d love to hear from you!


Recruitment process

  • 1st interview with our Talent Acquisition Manager, Margot

  • Then with our CPO, Rob.

Want to know more?

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