Data Scientist / AI Engineer

About lemlist

lemlist is the AI-powered sales engagement platform helping sales teams build pipeline smarter, not harder.

Bootstrapped from day one, we’ve grown from 0 to $50M+ ARR in 8 years without raising a single dollar. Today, 40,000+ sales teams use lemlist to book more meetings and close more deals.

We’re building the next generation of outbound: AI-first, multi-channel, highly personalized, and deeply integrated into the way modern sales teams work.

And we’re just getting started.

We’re looking for a Data Scientist / AI Engineer to join our team. You'll be responsible for identifying and shipping AI use cases that have a direct impact on the product and the business, working closely with Product and Engineering teams.

Your main mission will be:

• Identify where AI can create leverage across the product, propose concrete use cases, and take ownership from problem framing to production.
• Design, develop, and maintain LLM-based systems: prompt engineering, orchestration, retrieval pipelines, evaluation frameworks, observability…
• Deploy and operate AI models and infrastructure, including GPU server management and model serving.
• Design, train, evaluate, and maintain Machine Learning models in production.
• Support business and product teams with data-driven insights.

Key Results

Within 3 months, you will have/be:

• Successfully onboarded and integrated into the team.
• Have a clear understanding of the product, data, and existing AI systems.
• Audited existing LLM systems and ML models, identified quick wins and gaps.
• Shipped a first AI use case end-to-end in production.
• Set up or improved evaluation frameworks for at least one existing LLM system.

Within 12 months, you will have:

• Shipped several meaningful AI use cases that have a measurable impact on the product.
• Built a solid evaluation and observability layer across multiple LLM systems in production.
• Improved significantly the AI culture within lemlist.
• Supported the C-level (CEO, CPO, CMO, Head of Sales…) for strategic decisions.

What’s in it for you?

• Work in a profitable, bootstrapped, and high-growth company that doesn’t rely on external funding to live.
• Work on high-impact projects with highly skilled data profiles composed of a Senior Analytics Eng, a Senior Data Engineer and a Data Analyst that directly drive business decisions
• Collaborate directly with the C-suite on strategic topics
• Work with a team obsessed with speed, growth, and impact.

Preferred experience

Must have:

• 4+ years in a Data Science or AI Engineering role, ideally in a fast-moving environment.
• Advanced Python and SQL skills.
• Strong hands-on experience building and operating LLM-based systems: model APIs, agentic pipelines, RAGs, evaluation, and observability.
• Proficiency with agent-based frameworks such as LangChain.
• Hands-on experience with deep learning libraries (PyTorch, Transformers) and embeddings (SentenceTransformers).
• Experience deploying and managing models on cloud infrastructure (ideally GCP suite).
• Familiarity with CI/CD tools (Docker, Jenkins or equivalent).
• Strong interest in getting things into production.
• Strong analytical and problem-solving mindset.
• Fast learner, high ownership, structure, and execution speed.
• Fluent in French and English.
• Paris based (Paris office / remote).

Nice to have:

• Experience with workflow orchestration tools (Airflow or equivalent).
• Experience managing GPU servers for model training and serving.
• You have a first experience in B2B SaaS startup
• Knowledge of general IT good practices - maintainable and commented code, GitHub…

Additional information

• Competitive salary and company bonus (up to 18K€ per year depending on company’s performance)
• 38 days of holidays/year
• Alan Blue: Comprehensive 100% premium medical coverage for you and your family
• Swile Meal Tickets: Enjoy daily meal tickets to fuel productivity
• Navigo Card: Seamless commuting with a 100% covered Navigo card
• Gear: Get the laptop, tools, and equipment you need for your job
• Team building: We all meet once per year at really cool places around the world ()

Recruitment process