Senior Machine Learning Scientist

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

Senior Machine Learning Scientist | Core ML | UK (Hybrid)

Location: London | Type: Permanent

The Company

Our client is an established, tech-driven digital platform with an international footprint and millions of active users. Operating independently as part of a global group, they combine an agile, engineering-led culture with the backing and resources of a major parent business.

The Role

This is a high-visibility opportunity for an experienced Machine Learning Scientist to join a newly formed Core ML team and shape technical direction from day one. Reporting directly to the new Senior ML Engineering Manager, you will work closely with leadership to establish core architecture and team standards.

As a Staff Machine Learning Scientist, you will build foundational models that serve multiple engineering and product verticals—focusing on representation learning, visual embeddings, and generalized automated classifiers.

In this role, each Machine Learning Scientist on the team will look to you for technical strategy, complex engineering leadership, and mentorship while you collaborate directly with Product Managers, ML Engineers, and Data Scientists.

What You’ll Do

• Design, build, and deploy ML systems addressing multi-faceted platform challenges.
• Develop and fine-tune models for representation learning, vision tasks, and core classification, scaling them as shared services.
• Partner with senior stakeholders to define technical roadmaps for automated content understanding, risk/trust systems, and personalization.
• Drive large-scale, end-to-end experiment design—from initial hypothesis to production evaluation and business impact assessment.
• Evaluate emerging research, contribute to long-term data strategy, and foster engineering best practices across teams.
• Lead technical whiteboarding, architectural reviews, and roadmap planning sessions.
• Translate complex machine learning concepts into actionable strategy for cross-functional leadership.

What You’ll Bring

• A track record of shipping and scaling ML models with measurable commercial impact
• Deep ML knowledge applied in production, using PyTorch, TensorFlow or Transformers
• Strong, production-quality Python, plus solid data engineering and MLOps foundations
• Experience owning ML initiatives end to end, working through ambiguity, and mentoring othersStrong collaboration skills across multi-functional teams
• Real curiosity about AI and how it can improve the way you work

Nice to Have

• NLP, image classification, deep learning or LLM experience
• A/B testing and experiment design
• Experience building platform-style or shared ML systems
• Databricks and PySpark