ML Engineer

Flashmind Labs; Dubai; On-site; AED 240,000 - 420,000; Full time

Job summary

Flashmind Labs in Dubai is seeking engineers to own the data sourcing, processing, and scalable training pipelines, enabling researchers to iterate on architectures and objectives.

You will work with scientists and engineers to design and scale data ingestion, build distributed training infrastructure, and develop tooling for dataset inspection and quality monitoring. A strong background in Python and Rust, cloud platforms, and ML fundamentals is required.

Qualifications

• Bachelor's degree in Computer Science or related field.
• Proficiency in Python and Rust.
• Experience with cloud infrastructure (AWS, GCP, or Azure).
• Understanding of ML fundamentals and accelerator-based compute environments.

Responsibilities

• Designing and scaling data ingestion, cleaning, and processing pipelines
• Building and optimizing distributed training infrastructure
• Developing tooling for dataset inspection, curation, and quality monitoring
• Implementing efficient data loading and preprocessing for large-scale training workloads

Skills

Python

Rust

Cloud infra experience

ML fundamentals

Education

Bachelor's degree in CS or related

Tools

AWS

GCP

Azure

Kubernetes

Spark/Beam/Dask

Parquet/Arrow

Job description

About Flashmind Labs

We are building foundation models that engage with reality directly and evolve beyond their training data. Models that are calibrated, unconstrained in their pursuit of truth, and built for decisions with real consequences.

We are a focused team of researchers and engineers in Dubai. Come build the future of learning systems with us.

About This Role

The quality of our models depends directly on the quality of our infrastructure. We're looking for engineers to own the systems that source, process, and serve data at scale, and to build robust, efficient training pipelines. You will work at the intersection of data engineering and ML systems, ensuring our researchers can iterate fast on architectures and training objectives.

You will work with a team of scientists and engineers, including:

• Designing and scaling data ingestion, cleaning, and processing pipelines
• Building and optimizing distributed training infrastructure
• Developing tooling for dataset inspection, curation, and quality monitoring
• Implementing efficient data loading and preprocessing for large-scale training workloads

Minimum Qualifications

• Bachelor's degree or equivalent experience in Computer Science or a related field
• Proficiency in Python and Rust
• Experience with cloud infrastructure (AWS, GCP, or Azure)
• Understanding of machine learning fundamentals and accelerator-based (FPGA-like) compute environments

Preferred Qualifications

• Strong track record building and maintaining ML training infrastructure
• Experience developing, testing, and maintaining large-scale distributed systems
• Proficiency in data processing frameworks (Spark, Beam, Dask, or similar) and formats (Parquet, Arrow)
• Experience with Kubernetes and containerized workflows