Applied Scientist - AI ML

Global Software Solutions Group; Dubai; On-site; AED 360,000 - 600,000; Full time

Job summary

GSSTech Group in Dubai invites Applied Scientists to design, develop, and evaluate advanced AI/ML solutions across problem framing to production.

Ideal candidates will have strong foundations in ML, experience with PyTorch/TensorFlow, and ability to work with Data Engineers and MLOps to productionize models. We value Generative AI, LLMs, responsible AI, and collaboration in cross-functional Agile teams.

Qualifications

• Strong ML/AI foundations with experience across supervised/unsupervised learning, classification and regression.
• Hands-on experience with ML/DL models, evaluation, and feature engineering.
• Familiarity with production ML workflows and MLOps practices.

Responsibilities

• Translate business problems into well-defined ML problems with measurable success criteria.
• Design, develop, train, and evaluate ML/AI models per business requirements.
• Collaborate with Data Engineers, Software Engineering, and MLOps to productionise models.
• Contribute to model monitoring, lifecycle management, and responsible AI practices.
• Mentor junior scientists and contribute to technical leadership.

Skills

Python

ML/DL

NLP

Computer Vision

Generative AI

LLMs

Experimentation

PyTorch

TensorFlow

scikit-learn

Education

MSc/PhD in CS/ML/AI

Tools

PyTorch

TensorFlow

scikit-learn

Job description

Job Description

We are looking for Applied Scientists across different experience levels to design, develop, experiment with, and evaluate advanced AI/ML solutions that solve real-world business problems.

The role involves taking machine learning problems from problem framing and experimentation through model development, evaluation, and production deployment. Depending on experience, the successful candidate may also contribute to scientific leadership, mentor other team members, and help establish best practices across applied research and machine learning delivery.

We are looking for candidates with strong foundations in machine learning who can balance state-of-the-art techniques with practical business requirements, delivering reliable and measurable AI/ML solutions.

Key Responsibilities

• Translate business problems into well-defined machine learning problems with clear objectives and measurable success criteria.
• Design, develop, train, and evaluate machine learning and AI models based on business requirements.
• Apply appropriate techniques across areas including:
  • Classical Machine Learning
  • Deep Learning
  • Natural Language Processing (NLP)
  • Computer Vision
  • Generative AI
  • Large Language Models (LLMs)
• Define experimentation strategies, establish appropriate baselines, and conduct rigorous model evaluation.
• Perform statistical analysis, experimentation, error analysis, and model validation to assess model performance.
• Work closely with Data Engineers to define data requirements, feature pipelines, and dataset quality standards.
• Collaborate with Software Engineering and MLOps teams to productionise machine learning models and AI solutions.
• Contribute to model monitoring, performance tracking, model lifecycle management, and continuous improvement.
• Apply responsible AI principles, considering fairness, explainability, robustness, privacy, and reliability.
• Communicate technical findings, experimental results, trade-offs, and recommendations clearly to both technical and non-technical stakeholders.
• Contribute to technical documentation, research, experimentation, and knowledge-sharing activities.
• For experienced candidates, provide scientific leadership, review ML work, mentor junior scientists, and help raise the overall technical standard of the team.

Required Technical Skills – Machine Learning & AI

• Strong understanding of machine learning and deep learning concepts, including experience with relevant techniques across:
  • Supervised and unsupervised learning
  • Classification and regression
  • Model evaluation and validation
  • Feature engineering
  • Deep learning
  • NLP
  • Computer Vision
  • Generative AI / LLM-based applications

Experience With One Or More Of The Following

• PyTorch
• TensorFlow
• scikit-learn

Programming

• Strong proficiency in Python.
• Experience developing machine learning experimentation and modelling workflows.
• Ability to write clean, maintainable, and reproducible code.

Experimentation & Model Evaluation

• Strong understanding of experimental design.
• Statistical analysis and hypothesis-driven experimentation.
• Model evaluation and benchmarking.
• Baseline development.
• Error analysis.
• Model validation and performance optimization.

Production ML & MLOps

• Experience with taking ML models or AI solutions from experimentation into production, including:
  • Model deployment
  • Model monitoring
  • Model lifecycle management
  • MLOps workflows
  • Collaboration with engineering and data teams
  • Cloud-based machine learning environments

Experience with cloud ML platforms and MLOps tooling is highly desirable.

Generative AI / LLM Experience

Experience with Generative AI and LLM-based solutions will be highly valued, particularly experience taking such solutions beyond experimentation into production.

Relevant Experience May Include

• LLM-based applications
• Generative AI solutions
• Model evaluation
• Prompt-based experimentationAI application development
• Production deployment and monitoring of GenAI solutions

Responsible AI

• Fairness
• Explainability
• Robustness
• Privacy
• Model reliability
• Responsible model deployment

Collaboration & Stakeholder Management

• Work closely with Data Engineers, Software Engineers, MLOps teams, Product teams, and business stakeholders.
• Clearly communicate technical findings and modelling trade-offs.
• Translate complex scientific concepts into understandable recommendations for non-technical stakeholders.
• Collaborate effectively in cross-functional and Agile environments.

Leadership & Mentoring

• Provide scientific leadership within the squad.
• Review modelling approaches and scientific work.
• Mentor Applied Scientists and junior ML practitioners.
• Establish and promote strong experimentation and modelling practices.
• Contribute to the overall applied research and machine learning standards of the team.

Qualifications

• MSc or PhD in:
  • Computer Science
  • Machine Learning
  • Artificial Intelligence
  • Statistics
  • Mathematics
  • Data Science
  • or another relevant quantitative discipline
• Equivalent practical industry experience may also be considered.

Experience Levels

We welcome candidates across 0–15+ years of experience.

Junior / Entry-Level

• Strong academic foundation in ML/AI.
• Relevant MSc/PhD or equivalent project experience.
• Strong Python and ML framework knowledge.
• Research, thesis, internship, or practical ML project experience.

Mid-Level

• Independent ML model development.
• Strong experimentation and evaluation experience.
• Experience working with data and engineering teams.
• Exposure to production ML or MLOps environments.

Senior / Lead-Level

• End-to-end ownership of production ML solutions.
• Strong scientific and technical leadership.
• Experience with GenAI/LLM applications where relevant.
• Mentoring and scientific review capabilities.
• Strong stakeholder communication and decision-making skills.

Job Details

Role Level: Executive-Level

Work Type: Full-Time

Country: United Arab Emirates

City: Dubai

Company Website: https://www.gsstechgroup.com/

Job Function: Data Science & AI

Company Industry: IT Services and IT Consulting