Staff AI Engineer
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We are bsport. The place to be!
bsport is an all-in-one platform combining boutique fitness and advanced technology. Our platform helps our partners manage their bookings, payroll, marketing and more, to streamline operations and boost their commercial success.
Since we launched in 2019, we have already achieved the following:
- We’ve built a community of over 7 million users 🤝
- In December 2024 we have finalised the biggest Series B (€30 million)🏆
- Grown our team to more than 170 employees 🚀
We’re continuing to grow to become the #1 tech partner for boutique studios in Europe and the rest of the world!
Join us to write the next chapter of your career!
About the role:
As a Staff AI Engineer, you will architect and lead the development of bsport’s large-scale AI systems. You’ll be responsible for building the platforms, pipelines, and infrastructure that make cutting-edge AI/ML research usable, reliable, and scalable in production. You’ll collaborate with applied scientists and product teams to ensure that AI solutions deliver measurable business impact at scale.
🎯 What will be your impact:
- Architect, build, and optimize end-to-end ML/AI pipelines and framework: from data ingestion & preprocessing to model training, deployment, inference, and monitoring.
- Support and govern the development of AI agents ensure reliability of the agents across the organization
- Productionize AI/ML models with a focus on scalability, latency, and cost-efficiency.
- Design infrastructure for model lifecycle management: experiment tracking, versioning, reproducibility, monitoring, and alerting.
- Collaborate with applied scientists to integrate state-of-the-art research into robust production systems.
- Champion best practices in MLOps, CI/CD, and model governance.
- Mentor engineers; set engineering standards for AI/ML at bsport.
- Evaluate and integrate external AI/ML tools, frameworks, and APIs to accelerate development.
🌟You would be great fit if you have:
- 6+ years of experience in AI/ML engineering, data engineering, or MLOps with direct experience shipping AI/ML products to production.
- Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, JAX).
- Experience with modern MLOps toolchains (MLflow, Weights & Biases, Ray, Kubernetes, Airflow, etc.).
- Strong experience with Databricks.
- Proven expertise in building scalable, distributed data/ML systems on cloud platforms (AWS).
- Solid knowledge of API development, microservices, and production monitoring.
- Strong understanding of software engineering principles: testing, performance optimization, CI/CD.
- Collaborative mindset; able to partner with scientists, engineers, and product managers.
Nice to have
- Experience with LLM deployment (fine-tuning, retrieval augmentation, inference optimization).
- Background in recommendation, personalization, or forecasting systems.
- Familiarity with edge/low-latency inference and model optimization (quantization, distillation, pruning).
- Interest in AI safety, fairness, and ethical deployment.
🌈🌍 Diversity is one of our most valuable assets, and we are committed to fostering an inclusive environment where everyone can contribute their best work. We welcome applicants from all backgrounds, identities, and experiences to help us build a more inclusive, equitable team.
If you’re excited about this role but don’t meet every qualification, we encourage you to apply-curiosity, adaptability, and a willingness to learn are just as important to us as specific skills.
What We Offer
We believe great work comes from happy, supported people-that’s why we offer meaningful perks designed to promote balance, growth, and connection.
💵 Attractive compensation package
Competitive salary packages based on your experience and role.
💻 Work-Life harmony
Hybrid model with remote days to support balance and flexibility.
🌎 Work from anywhere
Enjoy up to 15 days of remote work from abroad each year.
🌍 Diverse fun loving team
Multicultural colleagues, after-work events, team-building & more.
- Departments
- Data
- Locations
- Paris
- Remote status
- Hybrid

Colleagues
Paris
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