Applied scientist in AI and machine learning at GSSTech Group in Dubai, United Arab Emirates

GroupGSSTech Groupin Dubai is accepting applications for applied scientists in AI and machine learning across multiple seniority levels, from entry level to lead, under a single listing that evaluates candidates on what they can demonstrate rather than years on the job.

Role:Applied Scientist in AI and Machine Learning at GSSTech Group, on site in Dubai, United Arab Emirates.

Core challenge:Taking an ambiguous business problem and turning it into a well-defined, measurable machine learning problem, then moving it from experimentation to a working production model. The job description highlights the stages where most projects stumble: experiment design, establishing an honest baseline, error analysis, statistical validation, and handoff to MLOps and software engineering teams, alongside post-launch performance monitoring and model lifecycle management. More senior candidates are additionally expected to provide technical leadership: reviewing peer work, mentoring junior scientists, and elevating the team's engineering standards.

Notable requirements:

• A solid foundation in machine learning and deep learning, spanning supervised and unsupervised learning, classification and regression, feature engineering, natural language processing, computer vision, and generative AI applications built on large language models.
• Experience with one or more frameworks such as PyTorch, TensorFlow, or scikit-learn, alongside the ability to choose the framework best suited to the problem rather than the newest one.
• Proficiency in Python and writing clean, reproducible code.
• Experience taking models into production: deployment, monitoring, lifecycle management, and working with cloud machine learning platforms.
• Documented experience in generative AI, particularly valued when it moves beyond experimentation into live deployment and monitoring.
• Practical awareness of responsible AI: fairness, explainability, robustness, privacy, and model reliability.

Salary:Not disclosed.

Practical step:Because the listing covers multiple experience tiers, define your seniority level yourself rather than leaving it to the screener. Choose a single project and outline it in four lines: the baseline you benchmarked against, the error your analysis uncovered, the decision you altered as a result, and the metric you tracked after release. Answering that last point clearly is what distinguishes someone who merely tested a model from someone who ran one in production.

Apply now: https://apply.workable.com/j/153C2CFBDF