Senior Technical Engineer (Data Science & ML)
Summary
Builds and tests AI/ML proofs of concept, including generative and agentic workflows, to validate business hypotheses and recommend go/no-go decisions.
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.