Junior Machine Learning Engineer Field Analytics for Mining

SFA (Oxford); England; On-site; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Competitive package

Job summary

SFA (Oxford) is seeking an energetic engineer/scientist to design, build and publish machine learning and applied AI systems used in mining, processing, HR and finance. The role involves working closely with safety, mining, geology and finance teams across multiple countries, including site visits, with a focus on practical impact on real operations.

The candidate will own data pipelines and ML workflows, handle sensor and drilling data, and interact with cross-disciplinary teams to translate

Qualifications

• Degree in physics, geophysics, engineering, applied mathematics, statistics, machine learning, data science or a closely related discipline
• Strong statistical grounding with model validation and uncertainty quantification
• Ability to reason about physical systems and challenging environments quickly
• Strong knowledge of ML and data science practices
• Familiarity with Python, Git and SQL
• Excellent presentation and written communication skills
• Willingness to travel internationally, including site visits
• Comfortable working across time zones with early mornings and late evenings
• Right to work in the UK (sponsorship position)
• Experience with time series, classification, survival analysis, or Bayesian methods
• Experience with sensor/IoT/drilling or industrial data
• Practical experience with LLM APIs or agent frameworks
• Rock mechanics/geomechanics/geoscience coursework
• Azure or another cloud platform
• Competitive package offered for the right candidate

Responsibilities

• Spend time with specialist teams and learn about supported operations
• Build and maintain data pipelines and production ML systems
• Analyse sensor, telemetry and operational data with statistical rigour
• Map real workflows and design agentic AI tools to automate them
• Present findings to technical and operational audiences, including senior stakeholders

Skills

Python

Git

SQL

Machine learning

Data science

Statistics

Time series

Classification

Survival analysis

Bayesian methods

LLM APIs

Agent frameworks

Rock mechanics

Geomechanics

Geoscience

Azure cloud

Education

Relevant degree (Physics / Geophysics / Engineering / Mathematics)

Tools

Azure cloud

Job description

SFA (Oxford) is seeking an energetic engineer/scientist to design, build and publish machine learning and applied AI systems used in mining, processing, HR and finance. The role involves working closely with safety, mining, geology and finance teams across multiple countries, including site visits, with a focus on practical impact on real operations.

The candidate will own data pipelines and ML workflows, handle sensor and drilling data, and interact with cross-disciplinary teams to translate