Principal ML Engineer 199877

Harnham; Paris; Hybride; EUR 120 000 - 150 000; Plein temps

Avantages offerts par ce poste

4.5-day week

Longevity bonus

Wellbeing initiatives

Career progression

Résumé du poste

Harnham in Paris is seeking a Principal Machine Learning Engineer to lead and shape ML strategy in a hybrid setting. You’ll balance technical leadership with hands-on model development in large-scale real-time systems across production environments.

Join a profitable AI-driven business focused on competitive ML infrastructure, recommender and bidding systems, and customer lifetime value modelling. The role offers progression, strong collaboration and a 4.5-day week with Friday afternoons off.

Qualifications

• Strong track record of delivering ML systems in production.
• Experience deploying models at scale in real-time environments.
• Excellent communication skills with technical and non-technical stakeholders.

Responsabilités

• Define technical direction for ML systems and frameworks.
• Design, develop and optimise ML models for large-scale production use.
• Lead the development of recommender engines, bidding algorithms and audience targeting systems.
• Build mobile attribution models and solutions focused on LTV and churn prediction.
• Drive MLOps best practices including model monitoring, observability and retraining.
• Enhance ML infrastructure, experimentation platforms and deployment processes.
• Collaborate with engineering leaders to align ML initiatives with business goals.
• Mentor engineers and influence architectural decisions across teams.

Connaissances

ML systems production

Model deployment at scale

Python

PyTorch

TensorFlow

MLOps

Recommendation systems

LTV modelling

Churn prediction

Real-time systems

Formation

PhD in STEM

Description du poste

Paris, France (Hybrid) | Up to €135,000 Base + Bonus (c.€150,000 OTE)

This is an opportunity to join a growing, profitable AI-driven technology business where machine learning is central to the product and commercial strategy. The role offers a rare blend of technical leadership and hands-on engineering, allowing you to shape the future direction of ML systems while solving complex challenges at scale.

The Company

They are an established technology scale-up that develops advanced machine learning solutions to power highly personalised digital experiences for millions of users worldwide. Operating internationally, the business has grown significantly in recent years and continues to invest heavily in its data and AI capabilities.

Their machine learning teams work on large-scale real-time systems where model performance directly impacts commercial outcomes. With a collaborative engineering culture and strong leadership support, they offer an environment where innovation and experimentation are encouraged.

The Role

As a Principal Machine Learning Engineer, you will provide technical leadership across the machine learning function while remaining closely involved in model development and production systems.

Key responsibilities include:

• Defining technical direction for machine learning systems and frameworks.
• Designing, developing and optimising machine learning models in a large-scale production environment.
• Leading the development of recommendation engines, bidding algorithms and audience targeting systems.
• Building mobile attribution models and solutions focused on customer lifetime value and churn prediction.
• Driving best practice across MLOps, model monitoring, observability and automated retraining.
• Enhancing machine learning infrastructure, experimentation platforms and deployment processes.
• Partnering with engineering leaders and business stakeholders to align machine learning initiatives with commercial objectives.
• Mentoring engineers and contributing to architectural decisions across the wider technology organisation.

Your Skills & Experience

• Strong commercial experience building and owning machine learning systems in production.
• Experience developing and deploying machine learning models at scale.
• Advanced Python skills alongside experience with modern machine learning frameworks such as PyTorch or TensorFlow.
• Excellent understanding of MLOps, model lifecycle management and production machine learning environments.
• Experience working with recommendation systems, predictive modelling, LTV modelling, churn prediction or related machine learning applications.
• Strong software engineering fundamentals with a focus on scalability, performance and reliability.
• Ability to communicate technical concepts effectively to both technical and non-technical stakeholders.
• Experience within AdTech, programmatic advertising, real-time bidding or demand-side platforms would be highly beneficial.

Nice to Have

• PhD in a STEM discipline.
• Experience within DSP environments.
• Exposure to mobile advertising, attribution modelling or related performance marketing technologies.

What They Offer

• 4.5-day working week with Friday afternoons off.
• Longevity bonus awarded every two years.
• Strong work-life balance and employee wellbeing initiatives.
• The opportunity to shape machine learning strategy within a growing and profitable technology business.
• Clear opportunities for progression and increased technical influence.

Interview Process

• Introductory conversation with the Talent Acquisition team.
• Take-home technical assessment.
• Technical interview and assessment review with senior machine learning engineers.
• Interview with the CTO.
• Final executive leadership interview.