Hiring.Camp

Senior Technical Engineer (Data Science & ML)

Kamayi

·

Jun 30, 2026

Location
Dubai
Type
Full-time
Department
Engineering
Seniority
Senior
Closing date
Jul 30, 2026
Source
CareersPage

Description

Senior Technical Engineer (Data Science / Machine Learning)

Location: Dubai, UAE (Client Site)

Salary: AED 14,000 – AED 17,000 / month

Benefits: Work visa, air tickets, medical insurance, gratuity, paid time off

Experience: 5–8 years of relevant experience

We're hiring a Senior Technical Engineer (Data Science / Machine Learning) to build and test AI and machine-learning proofs of concept scoped to real business requirements. The role rapidly prototypes models and agentic AI workflows, runs experiments to validate business hypotheses, and turns results into clear go/no-go recommendations. Work spans generative AI, agentic AI, and applied machine learning, with a focus on experimentation and fast iteration in a sandbox environment rather than production delivery.

Key Responsibilities

  • Build and test AI and machine-learning proofs of concept scoped to real business requirements and hypotheses.

  • Rapidly prototype models and agentic AI workflows, iterating quickly in a sandbox environment.

  • Design and run experiments to validate business hypotheses and measure feasibility, accuracy, and performance.

  • Apply generative AI and LLMs, including prompt engineering and retrieval patterns, to candidate use cases.

  • Perform data wrangling and feature engineering across structured and unstructured data sources.

  • Evaluate models and workflows against clear metrics, documenting findings, limitations, and trade-offs.

  • Turn POC results into clear go/no-go recommendations and hand-off notes for stakeholders.

Required Technical Skills

  • Strong Python for data science, with hands-on machine learning and deep learning.

  • Practical experience with generative AI and LLMs, agentic AI frameworks, and prompt engineering.

  • Data wrangling and feature engineering, plus solid SQL across relational data.

  • Model evaluation and experimentation, grounded in applied statistics.

  • Basic MLOps for experiment tracking, versioning, and reproducibility.

Candidate Profile

  • 5–8 years in data science / machine-learning roles, with a track record of taking ideas to working POCs.

  • Comfortable with ambiguity and fast iteration; biased toward experiments that produce clear answers.

  • Strong communicator — able to explain methods, results, and go/no-go calls to non-technical stakeholders.

Skills

PythonSQLMachine LearningDeep LearningData Science

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