Software Engineer - ML Quality

klarent.ai; Zürich; On-site; CHF 110,000 - 160,000; Full time

Job summary

Moonfire in Zürich seeks a Software Engineer – ML Quality to ensure AI agents are reliable and robust. You will design data pipelines, fine-tune models, and build evaluation frameworks. The role welcomes junior candidates with an MSc in CS and ML exposure, offering a path to grow into a pivotal ML quality function in a fast-moving startup.

Join a team of engineers building high-impact software with a strong emphasis on quality, ownership, and practical ML applications in a dynamic environment.

Qualifications

• Proven track record in ML quality, fine-tuning, or AI-powered product development.
• MSc in CS (or related field) with some ML exposure and eagerness to grow in ML quality.
• Knowledge of model training, evaluation, and common pitfalls.
• Experience building data collection, labeling, and annotation workflows.
• Analytical mindset with ability to spot weaknesses in models or data.
• Ability to explain technical concepts clearly to technical and non-technical audiences.
• Comfortable taking initiative in a fast-paced startup environment.

Responsibilities

• Design and build automated systems to collect, curate, and label training data for model fine-tuning.
• Fine-tune language models to improve accuracy, robustness, and performance based on real-world usage data.
• Implement robust evaluation pipelines to measure ML model performance against benchmarks.
• Collaborate with other engineers to establish quality metrics and acceptance criteria for new models and features.
• Investigate and debug model failures and performance regressions, identifying effective fixes.
• Help us build a world-class engineering culture that values quality, impact, and ownership.

Skills

Machine Learning Expertise

ML concepts understanding

Data pipeline skills

Problem-solving skills

Excellent communication

Bias for action

Education

MSc in Computer Science

Job description

The Opportunity

As a Software Engineer – ML Quality, you’ll be at the heart of ensuring our AI agents are not just functional, but reliable, accurate, and robust. You will help develop and implement training data collection, fine-tuning, and evaluation pipelines that drive continuous model improvement.

Your work will span monitoring live performance, curating high-quality datasets, retraining models to improve accuracy, and creating rigorous evaluation frameworks.

We’re open to junior candidates who may not have deep ML experience yet, as long as you bring strong programming skills, curiosity, and the determination to learn quickly. For junior applicants, an MSc in Computer Science or a related field with some exposure to machine learning is required.

What You’ll Do

• Design and build automated systems to collect, curate, and label training data for model fine-tuning.
• Fine-tune language models to improve accuracy, robustness, and performance based on real-world usage data.
• Implement robust evaluation pipelines to measure ML model performance against well-defined benchmarks.
• Collaborate with other engineers to establish quality metrics and acceptance criteria for new models and features.
• Investigate and debug model failures and performance regressions, identifying effective fixes.
• Help us build a world-class engineering culture that values quality, impact, and ownership.

About You

• Machine Learning Expertise: Proven track record in ML quality, fine-tuning, or AI-powered product development.
• Or: Strong programming background with an MSc in CS (or related field) and some ML exposure (coursework, research, internships), eager to grow in ML quality.
• Understanding of ML Concepts: Knowledge of model training, evaluation, and common pitfalls.
• Hands-on Data Pipeline Skills: Experience (or willingness to learn) building and maintaining data collection, labeling, and annotation workflows.
• Problem-Solving Skills: Analytical mindset with a knack for spotting weaknesses in models or data.
• Excellent Communication: Ability to explain technical concepts clearly to technical and non-technical audiences.
• Bias for Action: Comfortable taking initiative and working in a fast-paced startup environment.

Why Join Us?

• Make a real impact: Your work will be crucial in building the best quality AI product for software testing.
• Work with a talented team: Learn from ex-Google engineers who have built impactful products at scale.
• Competitive compensation: We offer a competitive salary, equity, and benefits package.
• Be a pioneer in AI: Be at the forefront of the agentic AI revolution and help shape the future of software testing.