23 days ago
Lausanne, SwitzerlandSenior
Responsibilities
- Design, develop, operate, and architect production-grade AI/ML systems, including LLM-powered applications, NLP models, RAG pipelines, and multi-agent systems.
- Make architectural decisions covering model selection, training strategies, fine-tuning, retrieval, orchestration, infrastructure, inference, latency, and cost optimization.
- Define online and offline evaluation frameworks, success metrics, automated evaluation pipelines, dashboards, monitoring, and production observability.
- Implement reproducible ML pipelines and manage deployment, monitoring, and lifecycle operations for models and AI artifacts.
- Optimize AI systems for scalability, performance, throughput, reliability, and cost using cloud and orchestration platforms.
- Collaborate with product managers, designers, software engineers, and data scientists to turn product requirements into incremental engineering plans.
- Propose new AI capabilities based on user insights and technology developments.
- Mentor junior AI engineers and establish engineering standards and AI best practices.
- Communicate complex AI concepts to technical and non-technical stakeholders.
Requirements
- Bachelor’s or master’s degree in Computer Science, Machine Learning, Data Science, or a related field.
- 5+ years of professional software engineering experience, including shipping and operating cloud services in production.
- Hands-on experience building LLM-powered production applications or ML/NLP applications.
- Strong proficiency in Python and AI frameworks, with strong understanding of machine learning fundamentals, optimization, and model evaluation.
- Experience with NLP systems such as embeddings, semantic search, retrieval systems, and text classification.
- Experience integrating and operating LLMs, including prompting, evaluation, observability, RAG, and agentic workflows.
- Hands-on MLOps experience with reproducible pipelines, experiment tracking, automated evaluation, and model or prompt delivery workflows.
- Knowledge of reinforcement learning, retrieval-augmented generation, and multi-agent AI architectures.
- Experience inspecting logs, designing metrics, and identifying production regressions.
- Proven AWS and cloud-based AI deployment experience.
- Strong communication skills in English and excellent problem-solving abilities in a collaborative, fast-paced environment.
- Preferred qualifications include scalable AWS or equivalent cloud infrastructure experience, model optimization for latency, throughput, and cost, large language model fine-tuning, multi-agent systems, orchestration frameworks, and enterprise or B2B AI systems experience.
Benefits
- Permanent contract with a competitive compensation package.
- Hybrid work model balancing office and remote work, with a structured onboarding approach for new hires.
- Flexible hours and unlimited paid time off in addition to 25 days of holidays.
- Three company-paid volunteer days.
- Access to a fitness centre inside the building.
- Reimbursement of the half-fare public transport travel card.
- Reimbursement of up to 50% of French class costs.
- Fresh fruit, cookies, and soft drinks.
- Regular company and team events, including volunteer days, talks, team-building activities, and office meetups.
- Referral bonuses after successful hires complete three months of continuous employment.
- Relocation package for employees moving from another country.
- Some benefits may not apply to temporary, contract, or internship roles.
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