# Lead Machine Learning Engineer – Recommendation Systems at GRAI

> Open job at GRAI in Warsaw, Poland. Workplace: Hybrid.

Source: Poland Dev Jobs, https://poland-devjobs.com/jobs/grai-lead-machine-learning-engineer-recommendation-systems-348ftc4
Posted 1 July 2026. Last checked on the employer's career site: 10 November 2026.

## Facts

- Company: [GRAI](https://poland-devjobs.com/companies/grai)
- Location: Warsaw, Poland
- Workplace: Hybrid
- Employment type: Full-time
- Polish: Not required
- Skills: LLMs, PyTorch, TensorFlow
- Not mentioned in the job post: salary, visa sponsorship, relocation, where you can apply from

## Job description

**GRAI** is a social music app out of Warsaw, currently in alpha. We’re building new ways to listen and respond through music - focusing on the social, human interactions that only happen when people are connected on both ends.

To make those connections truly resonant, we’re looking for a **Lead Machine Learning Engineer** to architect, build, and scale our recommendation and discovery engines. You’ll own the technical roadmap for our RecSys stack, transforming raw user behavior and social signals into deeply personalized, real-time experiences.

### What You’ll Do

- **Technical Leadership:** Define the long-term technical vision and architectural roadmap for our recommendation and personalization engines.
- **System Architecture:** Design and oversee the implementation of scalable retrieval, ranking, and re-ranking pipelines capable of handling massive user behavior and content data.
- **End-to-End Ownership:** Lead the development of robust ML infrastructure, including automated data processing, feature stores, MLOps, and real-time model monitoring.
- **Mentorship & Culture:** Mentor and coach a talented team of ML engineers, fostering a culture of technical excellence, continuous learning, and rigorous experimentation.
- **Data-Driven Strategy:** Design comprehensive offline evaluation frameworks and lead complex A/B testing strategies to validate and iterate on model performance.
- **Cross-Functional Collaboration:** Partner closely with Product and Engineering to align ML initiatives with high-level business metrics and product goals.

### What We’re Looking For

- **Proven Track Record:** Extensive experience designing, building, and scaling production-grade recommendation systems, search engines, or large-scale ranking models.
- **Technical Mastery:** Deep, foundational knowledge of machine learning, deep learning architectures, and modern information retrieval methodologies.
- **Scale & Infrastructure:** Significant experience with distributed data systems and modern ML frameworks (PyTorch, TensorFlow). Proven ability to handle massive, high-throughput user interaction datasets.
- **Production & MLOps:** Strong background in deploying and maintaining low-latency models in production, with a solid grasp of feature stores, model registries, and drift monitoring.
- **Leadership Skills:** Demonstrated experience leading technical projects, mentoring engineers, and successfully managing stakeholders without losing your hands-on technical edge.
- **Pragmatic Execution:** Ability to balance cutting-edge AI experimentation with the practical realities of production stability, latency constraints, and business value.

### Nice to Have

- **Real-Time Expertise:** Experience with streaming data architectures and real-time/session-based recommendation systems.
- **Domain Knowledge:** Background in audio processing, music streaming, or high-growth consumer-facing personalization products.
- **Advanced ML:** Familiarity with graph neural networks (GNNs), reinforcement learning, or leveraging Large Language Models (LLMs) for recommendation context.

### Why Join Us

- **High Autonomy & Impact:** Direct ownership over the technical direction of high-impact ML systems used by millions of users.
- **Founding-Stage Equity:** You’re joining a tight team at the alpha stage. We offer meaningful stock options so you have real skin in the game and share directly in the upside of what we build.
- **Influence the Future:** Shape not just the recommendation stack, but the broader engineering culture and hiring roadmap of a fast-growing startup.
- **Collaborative Innovation:** Work in a supportive, product-driven environment where your ideas directly dictate the future of how people experience music.
- **Rest & Recharge:** High-output work requires real downtime. We offer 26 business days of paid time off per year, plus 5 days off and Polish public holidays.

## How to apply

Apply on the job page, https://poland-devjobs.com/jobs/grai-lead-machine-learning-engineer-recommendation-systems-348ftc4: its Apply button opens the employer's own application page.

## More jobs from GRAI

- [Research Engineer](https://poland-devjobs.com/jobs/grai-research-engineer-52uhih3): GRAI, Warsaw, Poland. Hybrid. Posted 9 June 2026.
- [Senior Machine Learning Engineer (RecSys)](https://poland-devjobs.com/jobs/grai-senior-machine-learning-engineer-recsys-cksbi8x): GRAI, Warsaw, Poland. Hybrid. Posted 9 June 2026.