AI / ML Engineer - Recommendations Engine (Nyburs)

About Nyburs

Nyburs is building a trustable, creator-first social platform focused on high quality conversations and media. We are hiring a hands-on Senior AI / ML Engineer to own the recommendation problem end to end.

⚠️ Important :

We are only accepting candidates who have prior hands-on experience building recommendation systems in production.

What you will build

End-to-end recommendation pipelines : candidate generation, reranking, and post-ranking rules

Multi-modal feature extraction for images, short videos, and audio to power retrieval and ranking

Systems for offline training and online serving that meet product latency and scalability targets

Experimentation frameworks to measure impact and guardrails to preserve fairness and creator exposure

Production-grade monitoring and model lifecycle processes

Key responsibilities

Design, implement, and own recommender models and ML infrastructure

Translate product goals into modeling objectives and measurable metrics

Productionize multi-modal pipelines and low-latency serving solutions

Collaborate with product, backend, and data engineering on feature ingestion, training pipelines, and deployment

Run experiments, measure uplift, detect drift, and iterate on models

Implement fairness, diversity, and safety guardrails in ranking

Mentor and elevate junior engineers

Must have

4+ years hands-on experience building production ML systems

Prior experience building and deploying recommendation systems is mandatory (must have worked on recommender systems in the past 2-3 years)

Strong software engineering skills and comfort building production services and data pipelines

Practical experience with embeddings, approximate nearest neighbor retrieval, or other retrieval techniques

Experience with one or more deep learning frameworks and working with multi-modal data

Solid understanding of recommender evaluation metrics such as precision@k, recall@k, NDCG, CTR, watch time, and uplift measurement

Experience deploying models to production and designing for low latency

Strong product sense and ability to align technical work with business metrics

Nice to have

Experience with sequential or transformer-based recommenders or graph-based recommenders

Familiarity with streaming ingestion and feature stores

Background in social feeds, short form video, or creator platforms

Advanced degree in ML, CS, or related field

Knowledge of data science practices and tools, including statistical modeling, feature engineering, and experimentation analysis

Tech signals we value

Production ML and MLOps experience (model serving, monitoring, CI / CD)

Practical knowledge of vector / embedding retrieval and scalable retrieval architectures

Familiarity with model evaluation, A / B testing, and metrics-driven iteration

Compensation and benefits

Employee Stock Ownership Plans (ESOPs)

Comprehensive benefits package

Learning budget and conference support

Opportunity to shape product and influence ML roadmap from day one

Employment type

We welcome applications for contractual positions.

How to apply

Send your CV, a short note about a recommender project you built, and links to code or demos to careers@nyburs.com with subject : Senior AI / ML Engineer - Recs