Machine Learning Engineer / Data Scientist – Microsoft Azure

Open Positions: 1

Department: Data & AI Practice

Job Type: Full Time- In Office

Experience: 6+ years, including 3+ years of hands-on model development and production deployment

Preferred Certification: Microsoft Certified: Azure Data Scientist Associate (DP-100) or related Azure AI certification

Role: Machine Learning Engineer / Data Scientist - Microsoft Azure

Open Positions: 1

Department: Data & AI Practice

Location: Islamabad, Pakistan

Job Type: Full Time- In Office

Experience: 6+ years, including 3+ years of hands-on model development and production deployment

Preferred Certification: Microsoft Certified: Azure Data Scientist Associate (DP-100) or related Azure AI certification

SOL Gulf: Company Profile

SOL helps businesses modernize technology, optimize processes, and accelerate success so our clients stay ahead in a hyper-changing world. We are an ambitious team of technology experts with a vision to deliver world-class implementation of digital transformation and technology solutions. Based in Saudi Arabia, Pakistan and UAE, SOL combines global technology capabilities with local delivery excellence.

SOL Quick Facts

Established: 2017

Headquarters: SOL Gulf, Saudi Arabia

Regional Offices: Genesis Systems US, UAE, SOL Pakistan

Strategic Alliances: Microsoft, Google Cloud, Oracle, IBM

Website: www.solgulf.com

Role Overview

SOL Gulf is looking for a Machine Learning Engineer / Data Scientist with proven experience developing, deploying and operating machine learning models on Microsoft Azure.

This is a dedicated, full-time position for a leading energy and utilities organization in Saudi Arabia. The engineer will be fully allocated to the client, work from the client's backlog and be managed day to day by the client's technology team.

The role develops, validates, deploys and monitors machine learning models for business and operational use cases. The ideal candidate has delivered end-to-end ML solutions in complex enterprise environments, preferably in operational, energy, financial, asset-performance, forecasting, optimization or predictive-maintenance domains.

Key Responsibilities

1. Analytical Solution Design

• Translate analytical requirements into predictive and optimization solutions.
• Perform data preparation and feature engineering on large-scale structured and time-series datasets.

2. Model Development & Validation

• Train, test, validate and explain ML models, including regression, classification, clustering, time-series forecasting, anomaly detection and optimization models.
• Apply model explainability techniques so results can be understood and trusted by business users.

3. MLOps, Deployment & Integration

• Build pipelines for model versioning, deployment, retraining and monitoring using Azure Machine Learning and MLflow.
• Deploy models to managed endpoints and integrate them into business and operational workflows through APIs.
• Apply production MLOps practices using Git, Azure DevOps, CI/CD and Docker.

4. Documentation & Knowledge Transfer

• Prepare technical documentation and knowledge-transfer materials.
• Support client teams in adopting, operating and extending delivered solutions.

Qualifications & Experience

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Engineering or a related field.
• Minimum 6 years of data science or machine learning experience.
• At least 3 years of hands-on model development and production deployment.
• Experience delivering end-to-end ML solutions in complex enterprise environments.
• Experience with operational, energy, financial, asset-performance, forecasting, optimization or predictive-maintenance use cases is preferred.
• Relevant Azure Data Scientist or AI certifications are advantageous.
• Fluent English is required.

Technical Requirements

• Advanced Python skills, including pandas, NumPy, scikit-learn, and PyTorch or TensorFlow.
• Strong knowledge of regression, classification, clustering, time-series forecasting, anomaly detection, optimization and model explainability.
• Hands-on experience with Azure Machine Learning, including notebooks, experiments, pipelines, model registry, managed endpoints and monitoring.
• Strong SQL skills and experience with large-scale structured and time-series datasets.
• Experience with MLflow, Git, Azure DevOps, CI/CD, Docker, APIs and production MLOps.
• Experience with Microsoft Fabric, Spark or Databricks is preferred.

Competencies & Soft Skills

• Strong analytical problem-solving, framing business questions as measurable ML problems.
• Scientific rigor in model validation and honest communication of results and limitations.
• Production mindset with focus on versioned, monitored and maintainable models.
• Curiosity to learn operational and asset context quickly, such as plant, energy or financial processes.
• Comfortable working within a client team, client processes and client-managed backlog.
• Clear communication of model insights to non-technical decision makers.
• Commitment to high-quality documentation and knowledge transfer.

What We Believe

We have an unwavering commitment to diversity with the aim that every one of our people has a full sense of belonging within our organization. Inclusion and diversity are fundamental to our culture and help us bring different perspectives to the clients and communities we serve.

Equal Employment Opportunity Statement

SOL Gulf is an Equal Opportunity Employer. Employment decisions are based on role requirements, qualifications, experience and merit, in accordance with applicable laws and regulations.