Senior ML Scientist - Core ML (London, Hybrid)

NearTech Search; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

NearTech Search is seeking a Senior Machine Learning Scientist (Core ML) to help shape technical direction from day one in a hybrid London setting. You will build foundational models driving multiple product areas, mentor teammates, and collaborate with ML engineers and data scientists.

You will own architecture, set standards, and drive end-to-end ML initiatives—from representation learning to large-scale deployment—while partnering with Product Managers and leadership to align technical

Qualifications

• Experience shipping and scaling ML models with measurable commercial impact.
• Deep ML knowledge in production using PyTorch, TensorFlow or Transformers.
• Strong production-quality Python, plus data engineering and MLOps foundations.
• Experience owning ML initiatives end-to-end, through ambiguity, and mentoring others.
• Strong collaboration across multi-functional teams.

Responsibilities

• Design, build, and deploy ML systems addressing platform challenges.
• Develop and fine-tune models for representation learning, vision tasks, and core classification.
• Partner with stakeholders to define technical roadmaps for automated content understanding, risk/trust, and personalization.
• Lead end-to-end experiment design from hypothesis to production evaluation.
• Evaluate emerging research and foster engineering best practices across teams.
• Lead technical whiteboarding, architectural reviews, and roadmap planning.
• Translate complex ML concepts into actionable strategy for cross-functional leadership.

Skills

Shipping ML models

Production ML

Python programming

Mentoring others

Cross-functional collaboration

Tools

PyTorch

TensorFlow

Transformers

Databricks

PySpark

Job description

NearTech Search is seeking a Senior Machine Learning Scientist (Core ML) to help shape technical direction from day one in a hybrid London setting. You will build foundational models driving multiple product areas, mentor teammates, and collaborate with ML engineers and data scientists.

You will own architecture, set standards, and drive end-to-end ML initiatives—from representation learning to large-scale deployment—while partnering with Product Managers and leadership to align technical