Machine Learning Engineer, Dynamic Pricing & Optimisation
Eneba
Job Overview
Location
Remote
Salary
EUR 55,000 - 70,000 yearly
Employment Type
Full-time
Work Arrangement
Remote
Sector
Information Technology & Software
Experience Level
Mid-level (3-5 years)
About the Company
Eneba is dedicated to creating an open, secure, and sustainable marketplace for gamers worldwide. With over 20 million active users, Eneba offers unparalleled trust, safety, and market accessibility. The company is rapidly expanding its user base and diversifying its offerings, aiming to grow alongside the vibrant gaming community.
The company fosters a culture of innovation and continuous improvement, driven by a talented international team. Eneba provides opportunities for personal and professional growth, supported by clear feedback and promotion processes. Employees are encouraged to work from a location of their choice, whether in an office, remotely, or while traveling.
Job Description
Eneba is seeking a skilled Machine Learning Engineer to spearhead the optimization of our dynamic pricing strategies. This role offers the chance to take complete ownership of our Featured Offers pricing algorithm, driving direct revenue improvements through sophisticated ML models.
You will be responsible for building and refining models that predict user willingness to pay and price elasticity, leveraging behavioral signals and market data. Collaboration with Product and Marketing teams will be key to defining effective pricing strategies for campaigns and placements.
This position involves defining and tracking crucial metrics that link model performance to business KPIs, such as revenue per session and promotional ROI. You will work closely with engineering teams to deploy pricing models as low-latency APIs and ensure their ongoing performance through diligent monitoring and alerting.
To apply for this role, click the Apply button on this page and follow the instructions.
Required Skills
Key Responsibilities
- Own and continuously improve Eneba's Featured Offers pricing algorithm — from model design through experimentation to production monitoring
- Build and iterate on willingness-to-pay and price elasticity models using behavioral signals: purchase history, browsing patterns, session data, price sensitivity indicators
- Collaborate with Product and Marketing/Growth to define pricing strategies for promotional campaigns and featured placements
- Define and track evaluation metrics connecting model output to business KPIs — revenue per session, conversion rate, margin, promotional ROI
- Work with Data Platform and Backend Engineering to ship pricing models as low-latency APIs integrated into live marketplace surfaces
- Monitor deployed models for data drift, distribution shifts, and degradation; own observability and alerting
- Contribute pricing-relevant features to the feature store — user price sensitivity signals, historical purchase behavior, category-level demand indicators
Qualifications
- Hands-on production experience building models that optimize pricing decisions — promotional pricing, demand-based pricing, or personalized pricing. You've shipped something that moved a revenue number.
- Experience modeling willingness to pay, price elasticity, or conversion probability as a function of price. You're comfortable working with implicit signals and sparse, noisy data.
- End-to-end ML ownership — you've taken models from raw data through feature engineering, training, evaluation, API deployment, and production monitoring. You don't hand off at the notebook stage.
- Strong Python and MLOps fluency — extensive Python for model development, plus experience with MLOps tooling (MLflow or similar) for experiment tracking, model versioning, and lifecycle management.
- Good English level is required, proficiency is preferred.
Benefits & Perks
- Opportunity to join our Employee Stock Options program.
- Opportunity to help scale a unique product.
- Various bonus systems: performance-based, referral, additional paid leave, personal learning budget.
- Paid volunteering opportunities.
- Work location of your choice: office, remote, opportunity to work and travel.
- Personal and professional growth at an exponential rate supported by well-defined feedback and promotion processes.
How to Apply
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This role is crucial for optimizing Eneba's revenue through advanced pricing strategies. You will take full ownership of the pricing algorithm, developing models that understand user price sensitivity and willingness to pay. Your work will directly impact revenue by improving pricing for featured offers and promotional campaigns.
Posted Date
March 23, 2026
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