Machine Learning Engineer: Ranking & Personalization

Jobgether Srl; Lisboa; Remote; EUR 71,000 - 107,000; Full time

Benefits offered by this job

Fully remote work

Unlimited vacation

Home office stipend

Apple laptops provided

Annual training budget

Job summary

Jobgether Srl seeks a Machine Learning Engineer focused on Ranking and Personalization in a predominantly remote setup. You will design, implement, and maintain real-time ML services powering e-commerce search, discovery, and shopping experiences for users worldwide.

You will collaborate with engineering, data, and business teams to leverage user behavior and experiments, driving measurable improvements in conversion and revenue. The role emphasizes ownership, quality, and scalable solutions.

Qualifications

• 3+ years in applied machine learning with real‑world deployment.
• Strong Python and SQL skills, plus big data tech competence.
• Experience in production personalization, ranking or recommender systems.

Responsibilities

• Design, build, deploy real-time ML services for ranking and personalization.
• Improve personalized shopping experiences using user behavior data.
• Experiment, run A/B tests, and translate results into product improvements.
• Collaborate with engineers and stakeholders to deliver scalable solutions.
• Communicate findings and ensure reliable production systems.

Skills

Python

SQL

Big data

A/B testing

English comms

Cross-functional teamwork

Model deployment

Job description

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Machine Learning Engineer: Ranking & Personalization based in Portugal. Join a collaborative, AI-driven environment where machine learning powers smarter e-commerce search, discovery, and shopping experiences. In this role, you will design, build, and maintain high-performance, real-time personalization services that reach hundreds of millions of users worldwide.

You will work closely with engineers, data specialists, and business stakeholders to develop innovative solutions that improve product discovery and customer engagement. By leveraging user behavior, experimentation, and advanced machine learning techniques, you will help deliver more relevant shopping experiences. Your work will directly contribute to measurable business outcomes, including improved conversion rates and revenue growth.

This is an opportunity to combine technical expertise, analytical thinking, and a strong sense of ownership while making a meaningful impact in a supportive, remote-first team. Accountabilities

Accountabilities

• Design, develop, deploy, and maintain scalable, real-time machine learning services that power ranking and personalization across e-commerce products, platforms, and industry verticals.
• Enhance personalized shopping experiences by developing and refining recommendation, ranking, and discovery capabilities based on user behavior and preferences.
• Analyze user interactions and behavioral data to build effective models that deliver more relevant and engaging customer experiences.
• Research, evaluate, and implement different personalization approaches to identify solutions that maximize customer value and business performance.
• Formulate and validate hypotheses through experimentation and A/B testing, measuring the impact of personalization improvements on key business metrics.
• Collaborate with engineering teams, including ranking specialists, as well as cross-functional technical and non-technical stakeholders to develop and continuously improve personalization features.
• Communicate findings, technical decisions, and business outcomes clearly to stakeholders, translating complex machine learning concepts into actionable insights.
• Take ownership of problems from investigation through implementation, continuously improving the reliability, scalability, and effectiveness of production systems.

Requirements:

• At least 3 years of professional experience in applied machine learning, with a strong understanding of how to develop and deploy ML solutions in real-world environments.
• Proficiency in Python, SQL, and big data technologies, with the ability to support end-to-end machine learning product development.
• Proven experience building, deploying, and maintaining production-grade personalization, recommendation, or ranking systems.
• Practical knowledge of designing and analyzing A/B tests and using experimental results to guide product and model improvements.
• Experience with a major public cloud platform is an advantage.
• Strong analytical and problem-solving skills, including the ability to investigate complex challenges, identify root causes, and translate findings into practical solutions.
• Excellent English communication skills, with the ability to explain technical concepts and demonstrate business value to diverse stakeholders.
• Experience working effectively in cross-functional teams, balancing technical priorities with product and business objectives.
• Ability to work autonomously, manage responsibilities independently, and take initiative in identifying opportunities for improvement.
• A proactive, collaborative mindset, combined with empathy, accountability, and a genuine interest in delivering impactful machine learning solutions.

Competitive compensation:

• Annual base salary ranging from
• $80,000 to $120,000 USD, depending on skills, experience, qualifications, and interview results.
• Stock options:
• Equity opportunities in addition to the base salary.
• Fully remote work:
• Work remotely and choose where you live.
• Flexible time off:
• Unlimited vacation, with employees strongly encouraged to take at least three weeks off annually.
• Home office support:
• A work-from-home stipend to help you create a comfortable and productive workspace.
• Equipment provided:
• Apple laptops supplied to new employees.
• Learning and development:
• An annual training and development budget to support professional growth.
• Family support:
• Maternity and paternity leave for eligible employees.
• Regular team offsites that encourage collaboration, relationship-building, and shared learning.
• Supportive culture:
• Work alongside talented, empathetic colleagues in an open and cooperative environment that values ownership, inclusion, and meaningful impact.

Machine Learning Engineer: Ranking & Personalization Lisbon, Portuguese Republic, PT