Job Details

Experience Needed:5 To 7 Years

Career Level:Experienced (Non-Manager)

Education Level:Not Specified

Salary:Confidential

Job Categories:

• IT/Software Development

Skills And Tools:

LLMs/generative AI (prompting, fine-tuning, retrieval).Real-time inference optimization (GPU/CPU serving, A/B rollouts, autoscaling).Reinforcement learning exposure.Open-source contributions or peer-reviewed publications.

Job Description

AEPG is seeking a talented and well experienced Ai engineer who meets the below criteria ,please read it very carefully

What you’ll do

 

 

Design, train, and evaluate models (NLP/CV/reco) that solve defined business problems; track accuracy/latency KPIs.

 

 

Productionize models with CI/CD, containers, and monitoring to reach >99% service uptime.

 

 

Build/maintain data pipelines with data engineering to improve freshness SLAs and model quality.

 

 

Run experiments (offline/online), analyze errors, and reduce false positives/negatives through focused iteration.

 

 

Optimize inference (batch/real-time), including quantization and caching, to cut latency while controlling cost.

 

 

Document architectures, experiments, and decisions for reproducibility and review.

 

 

Contribute to internal tooling, MLOps standards, and model governance (privacy, fairness, interpretability).

 

 

 

 

Job Requirements

Must-haves (hard criteria)

 

 

5+ years full-time, post-graduation, non-intern experience in AI/ML engineering.

 

 

3+ years hands-on with PyTorch or TensorFlow (production use).

 

 

2+ end-to-end model deployments to production (data → training → deploy → monitor).

 

 

Strong Python; solid SQL and data preprocessing/feature engineering.

 

 

Cloud experience (AWS/GCP/Azure) and MLOps (Docker, Kubernetes, experiment tracking such as MLflow).

 

 

Experience integrating models behind REST/GRPC services and instrumenting for observability.

 

 

Where you’ll excel

 

 

Outcome focus: you quantify impact and close the loop from metric to roadmap.

 

 

Pragmatic engineering: you ship resilient systems and de-risk iteratively.

 

 

Clear communication: you align with product, data, and infra to land changes safely.

 

 

Location / work model / time zone / travel

 

 

Onsite — Egypt (Africa/Cairo time zone). Core hours follow local business hours. Travel not expected.

 

 

Compensation & benefits

 

 

Competitive package and learning/professional development support. Collaborative, inclusive team environment.

 

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