Remote GenAI & LLM ML Engineer

Machine Learning Engineer (GenAI & LLM) – Remote (Switzerland‑Based)

Company Overview
We are a fast‑growing, tech‑driven organization headquartered in Switzerland, delivering cutting‑edge AI‑powered products and services to a global clientele. Our mission is to harness the power of generative AI and large language models (LLMs) to create intelligent, scalable solutions that transform industries.

Role Summary
We are looking for a Machine Learning Engineer with 2–8 years of hands‑on experience to design, develop, and operationalize ML models—especially generative AI and LLM‑based solutions. You will work closely with product managers, data scientists, software engineers, and UX designers to turn research prototypes into production‑ready AI agents that deliver measurable business value.

Key Responsibilities

Area	What You’ll Do
Model Development	• Design, train, and fine‑tune large language models (e.g., GPT‑style, BERT, T5) and other generative AI architectures. • Implement custom tokenizers, prompt‑engineering pipelines, and retrieval‑augmented generation (RAG) workflows.
Production & Deployment	• Containerize models with Docker / OCI and orchestrate them on Kubernetes or serverless platforms (e.g., AWS SageMaker, GCP Vertex AI, Azure ML). • Build CI/CD pipelines for model versioning, automated testing, and seamless roll‑outs.
Performance Optimization	• Profile inference latency, memory footprint, and cost; apply quantization, pruning, distillation, and hardware‑specific acceleration (GPU/TPU/CPU). • Implement monitoring, logging, and alerting for model drift and degradation.
Collaboration	• Partner with cross‑functional teams to translate product requirements into ML specifications. • Mentor junior engineers and contribute to shared codebases, documentation, and best‑practice guidelines.
Research & Innovation	• Stay current with the latest GenAI research, evaluate emerging models, and prototype novel solutions that can be productized.
Compliance & Ethics	• Ensure models meet data‑privacy regulations (GDPR, Swiss data protection) and adhere to responsible AI principles.

Required Qualifications

Skill	Details
Experience	2–8 years of professional experience building, deploying, and maintaining ML models in production.
Programming	Expert‑level Python; comfortable with libraries such as PyTorch, TensorFlow, JAX, Hugging Face Transformers, and Scikit‑learn.
ML Foundations	Strong grasp of supervised/unsupervised learning, deep learning architectures, optimization algorithms, and evaluation metrics.
GenAI & LLMs	Hands‑on experience with large language models, prompt engineering, fine‑tuning, and retrieval‑augmented generation.
DevOps / MLOps	Proficiency with Docker, Kubernetes, CI/CD (GitHub Actions, GitLab CI), model registries, and cloud ML services (AWS, GCP, Azure).
Data Engineering	Ability to work with large, semi‑structured datasets (JSON, Parquet) and use tools like Spark, Dask, or Pandas.
Problem Solving	Proven track record of diagnosing complex model issues and delivering robust, scalable solutions.
Communication	Excellent written and verbal English; ability to convey technical concepts to non‑technical stakeholders.
Education	Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Statistics, or a related field (PhD is a plus).

Nice‑to‑Have

• Experience with reinforcement learning from human feedback (RLHF) or instruction‑tuned models.
• Familiarity with LangChain, LlamaIndex, or other LLM‑orchestration frameworks.
• Knowledge of Swiss data‑privacy law and responsible AI guidelines.
• Contributions to open‑source ML projects or publications in top conferences.

What We Offer

• Fully Remote work arrangement (Swiss‑based time zone alignment).
• Competitive salary (aligned with experience) + performance‑based bonuses.
• Generous equipment budget (laptop, monitors, ergonomic accessories).
• Continuous learning stipend for conferences, courses, and certifications.
• Flexible vacation policy and a supportive work‑life balance culture.
• Opportunity to shape the next generation of AI products used by thousands of customers worldwide.

How to Apply

1. Prepare an up‑to‑date résumé highlighting relevant ML projects, especially any work with generative AI or LLMs.
2. Include a brief cover letter (max 300 words) explaining why you’re excited about this role and how your experience aligns with the responsibilities.
3. Provide links to any public code repositories (GitHub, GitLab) or published papers that showcase your expertise.

Submit your application to ml‑engineer@yourcompany.ch with the subject line:

[Machine Learning Engineer – GenAI] – Your Full Name

We will review applications on a rolling basis and reach out to qualified candidates for an initial video interview.

Join us and help build the AI agents that will define the future of intelligent products!

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