AI Engineer

2 days ago

Istanbul, Istanbul, Turkey Randstad Türkiye Full time $60,000 - $120,000 per year

About the Role

We are seeking a skilled
AI Engineer
with hands-on experience in
LLM deployment
,
fine-tuning
,
and cloud-based AI workflows.
This is a full onsite position, and candidates must have
no international travel restrictions
, as the role may require short-term overseas assignments.

Fluent English
communication is mandatory for this position due to international project collaborations.

Key Responsibilities:

  • Develop, fine-tune, and optimize
    Large Language Models (LLMs) and Computer Vision (CV)
    for production use
  • Deploy AI models in production using Docker,
    container-based environments,
    and CI/CD workflows
  • Build and maintain scalable inference pipelines and AI-driven APIs
  • Manage workloads in
    cloud environments
    (AWS, GCP, Azure, Huawei Cloud, etc.)
  • Improve model accuracy, performance, and efficiency through evaluation and optimization
  • Implement data preprocessing, model training, and experiment tracking workflows
  • Collaborate closely with cross-functional teams and communicate effectively in
    English
  • Troubleshoot model, infrastructure, and deployment-related issues
  • Work
    onsite
    and participate in
    international travel
    when required

Required Qualifications:

Min 2–3 years
of professional experience in AI Engineering / ML Engineering / LLM Engineering

Strong, practical experience with
LLM deployment
, serving frameworks, and inference optimization

Hands-on experience in LLM fine-tuning (LoRA, QLoRA, instruction tuning, RLHF/DPO, etc.)

Strong programming skills in Python; experience with PyTorch or TensorFlow

Proficiency with Docker and
containerized application development

Experience with
cloud platforms
(AWS / Azure / GCP / Huawei Cloud)

Familiarity with MLOps tools (Git, CI/CD, model registry, experiment tracking)

Fluent in
English
, both written and spoken

No restrictions on
international travel

Willingness to work full-time
onsite
(not remote)

Preferred Skills (Nice to Have):

Experience with distributed training, model parallelism, or
GPU
clusters

Familiarity with
Kubernetes
and cloud-native
AI infrastructure

Experience with
vLLM
, Hugging Face ecosystem, or similar serving technologies

Knowledge of vector databases, embeddings, and
RAG
systems

Strong
Linux
system skills (bash scripting, process management, system monitoring, environment setup, troubleshooting)

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