ML Engineer

Flashmind Labs; Dubai; On-site; AED 300,000 - 540,000; Full time

Job summary

A tech innovation company in Dubai is looking for engineers to enhance their ML training infrastructure. The role involves designing data ingestion systems and optimizing training infrastructure. Candidates should possess a Bachelor’s degree in computer science or a related field, with proficiency in Python and Rust. Experience with cloud platforms and machine learning fundamentals is crucial. Join a focused team to help shape the future of learning systems.

Qualifications

• Bachelor's degree or equivalent experience required.
• Proficient in Python and Rust programming languages.
• Experience with cloud infrastructure like AWS, GCP, or Azure is essential.
• Understanding of machine learning fundamentals and accelerator-based compute environments.

Responsibilities

• Design and scale data ingestion, cleaning, and processing pipelines.
• Build and optimize distributed training infrastructure.
• Develop tooling for dataset inspection, curation, and quality monitoring.
• Implement efficient data loading and preprocessing for large-scale training.

Skills

Proficiency in Python

Proficiency in Rust

Understanding of machine learning fundamentals

Experience with cloud infrastructure

Strong track record building ML training infrastructure

Familiarity with data processing frameworks

Experience with Kubernetes

Education

Bachelor's degree in Computer Science or a related field

Tools

AWS

GCP

Azure

Spark

Beam

Dask

Job description

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

Apply for this role

Due to the volume of applications, we're only able to respond to candidates we'd like to follow up with.