Staff Machine Learning Scientist (Applied AI, Remote)

Jobgether; United Kingdom; Remote; GBP 80,000 - 100,000; Full time

Job summary

A global remote team seeks a Staff Machine Learning Scientist to architect and deploy AI solutions. This role involves analyzing complex datasets, prototyping models, and working with cross-functional teams. The ideal candidate has extensive experience in machine learning, strong programming skills in Python, and a Master's or PhD in a related field. This position offers a competitive salary and a flexible, remote-first culture.

Benefits

100% remote position

Flexible schedules

Competitive salary

Equity options

Annual learning stipend

Qualifications

• 10+ years of hands-on experience with ML and statistical modeling.
• Advanced understanding of LLM and SLM architectures and fine-tuning methods.
• Excellent communication skills for translating technical outputs into business narratives.

Responsibilities

• Partner with teams to design AI-powered data products.
• Explore and analyze complex datasets using ML techniques.
• Prototype and operationalize models for NLP and predictive analytics.

Skills

Machine Learning

Statistical Modeling

Deep Learning

Python

NLP

SQL

Data Visualization

MLOps

Education

Master's or PhD in Computer Science, Data Science, Statistics, or a related field

Tools

PyTorch

TensorFlow

AWS

Azure

Job description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Machine Learning Scientist (Applied AI) in EMEA.

Join a global, fully remote team driving innovation at the intersection of machine learning and data intelligence. In this role, you'll architect and deploy advanced AI solutions that transform complex real-world datasets into powerful, actionable insights. Your work will directly shape the next generation of intelligent data products-enhancing product quality, user experience, and business decision-making for global clients. This position offers the opportunity to build from the ground up, experiment with emerging AI techniques, and make a measurable impact in a collaborative, fast-paced environment that values curiosity, creativity, and excellence.

Accountabilities

• Partner with engineering and product teams to design, develop, and deploy AI-powered data products at scale.
• Explore, model, and analyze complex datasets using advanced statistical, machine learning, and deep learning techniques.
• Prototype, validate, and operationalize models for NLP, recommendation systems, anomaly detection, and predictive analytics.
• Research and apply cutting-edge methods, including LLMs, fine-tuning (LoRA, QLoRA, SFT), and scalable inference strategies.
• Translate technical results into clear, actionable business insights for non-technical stakeholders.
• Continuously evaluate and enhance model accuracy, fairness, and robustness through experimentation and optimization.
• Contribute to defining standards, best practices, and tools that strengthen the company's data science culture and capabilities.

Requirements

• Master's or PhD in Computer Science, Data Science, Statistics, or a related field.
• 10+ years of hands-on experience applying ML and statistical modeling to real-world data problems, ideally within SaaS or data-centric products.
• Strong programming skills in Python, with deep expertise in frameworks such as PyTorch and TensorFlow.
• Proven experience in NLP, predictive modeling, recommendation systems, anomaly detection, and MLOps deployment.
• Proficiency in SQL, data visualization tools, and cloud environments (AWS or Azure).
• Advanced understanding of LLM and SLM architectures, training, and fine-tuning methods.
• Excellent communication skills with the ability to translate technical outputs into clear business narratives.
• A collaborative, curious, and growth-oriented mindset with a passion for experimentation and innovation.

Benefits

• 100% remote position across select EMEA countries.
• Flexible schedules and supportive remote‑first culture.
• Competitive salary and comprehensive total rewards package.
• Equity options and annual learning stipend to support continuous growth.
• Inclusive, diverse team environment with strong representation and belonging.
• Opportunities to work with cutting‑edge datasets and shape next‑generation AI solutions.