Senior ML Engineer at Nexthink
May no longer be active — verify on the employer site
At a glance
- Company
- Nexthink
- Location
- Lausanne, Switzerland
- Work arrangement
- On-site
- Employment type
- Full-time
- Experience
- 5–10 years
- Working hours
- 40 hours
- Visa sponsorship
- Offered, according to the listing
- Posted
- Added to The Stack
✨ The Stack take on this Nexthink job
Updated 2026-11-05, from our data and official sources.
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About the role
Responsibilities:
- Design and implement scalable AI products with a focus on agentic systems and LLM integration.
- Define evaluation frameworks and success metrics for LLMs and multi-agent behaviours.
- Build and operate MLOps pipelines: training, fine-tuning, validation, deployment, monitoring and rollback.
- Implement reproducible CI/CD for models, prompts and embedding configs; integrate feature stores and automated evaluations.
- Collaborate closely with software engineers, data scientists and product to translate business needs into robust AI features.
- Mentor and coach junior engineers; drive knowledge sharing and best practices across the team.
- Troubleshoot model quality regressions by inspecting logs, designing metrics and iterating on data and model changes.
Requirements:
- BSc/MSc in Computer Science, ML, Data Science or related discipline.
- 5+ years building LLM-powered production applications and agentic systems.
- Strong Python skills and hands-on experience with frameworks like LangChain and PyTorch.
- Proven experience deploying cloud-based AI on AWS and operating models in production.
- Familiarity with RL, RAG, multi-agent architectures and model fine-tuning techniques.
- Practical MLOps knowledge: reproducible pipelines, feature stores, CI/CD, monitoring and automated evaluations.
- Strong data intuition, problem-solving, and clear communication for technical and non-technical stakeholders.
Responsibilities
You will lead the design and deployment of scalable AI-powered products, with a specific focus on agentic systems and LLM integration. Additionally, you will implement MLOps practices and mentor junior engineers to foster a culture of technical excellence.
Requirements
Candidates must hold a degree in Computer Science or a related field and possess at least 5 years of hands-on experience with LLM-powered production applications. Proficiency in Python, AI frameworks, and cloud-based deployments is essential, along with strong communication skills.
Key skills
- Python — in 1200 other listings on The Stack
- Machine learning — in 291 other listings on The Stack
- LLM — in 51 other listings on The Stack
- LangChain — in 19 other listings on The Stack
- PyTorch — in 92 other listings on The Stack
- AWS — in 802 other listings on The Stack
- MLOps — in 72 other listings on The Stack
- Reinforcement learning — in 22 other listings on The Stack
- RAG
- Multi-agent AI architectures
- CI/CD
- Feature stores
- Model fine-tuning
- Data intuition
- Mentorship
On The Stack (as of 2026-11-05)
Frequently asked questions about Nexthink
Is this Senior ML Engineer role still open?
It was posted on 2026-04-24. Listings more than 30 days old may no longer be active, so check Nexthink's site before applying.
Does Nexthink offer visa sponsorship?
This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Nexthink's site.
Where is this role located?
The listing gives the location as Lausanne, Switzerland. It is marked on-site.
What skills does this role ask for?
The listing names: Python, Machine learning, LLM, LangChain, PyTorch, AWS, MLOps, Reinforcement learning, RAG, Multi-agent AI architectures, CI/CD, Feature stores, Model fine-tuning, Data intuition, Mentorship.