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RD
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Cynet Systems

GEN AI Specialist

Montreal, QC, Canada

$50 to $55 CAD / hour · Contract

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Job details

Pay: $50 to $55 CAD / hour
Job type: Contract
Apply by: Nov 8, 2026
Posting language: English
Posted: Oct 9, 2026

Original job description

Job Overview

Pay Range: $50.00hr - $55.00hr

Requirement/Must Have

8+ years of experience in data science or AI engineering.
2+ years of dedicated experience in Generative AI.
Deep expertise in PyTorch, TensorFlow, or JAX.
Hands-on experience with Hugging Face, LangChain, LlamaIndex, and vLLM.
Mastery of Python for performance tuning.
Deep understanding of regression, clustering, decision trees, and ensemble methods.
Strong grasp of Transformers, CNNs, RNNs, and reinforcement learning (RLHF).
Experience with Vector Databases such as ChromaDB, Pinecone, or Milvus.
Proficiency with SQL and NoSQL databases.
Experience with MLflow, Kubeflow, or Triton Inference Server.
Proficiency with AWS (SageMaker), Azure (Azure AI), or GCP (Vertex AI).
Experience with GPU acceleration and CUDA.

Responsibilities

Design and deploy Generative AI solutions using Large Language Models (LLMs) and diffusion models.
Implement optimization techniques including prompt engineering, fine-tuning, and Retrieval-Augmented Generation (RAG).
Develop predictive models by selecting, training, and tuning traditional machine learning and deep learning algorithms.
Build scalable pipelines for data preprocessing, feature engineering, and model training.
Optimize AI frameworks to improve inference speed, reduce latency, and lower compute costs.
Integrate AI models seamlessly into production software architectures and enterprise workflows.

Skills

Python.
Generative AI (GenAI).
Large Language Models (LLMs).
Prompt Engineering.
Fine-tuning LLMs.
Retrieval-Augmented Generation (RAG).
PyTorch.
TensorFlow.
JAX.
Hugging Face.
LangChain.
LlamaIndex.
vLLM.
Machine Learning.
Deep Learning.
Transformers.
CNNs.
RNNs.
RLHF.
Vector Databases.
MLOps.
CUDA.

Qualification And Education

Master s degree in Computer Science, Data Science, Mathematics, or a related quantitative field.

Benefits

Our Benefits Include:

Medical, Dental, and Vision Insurance
401(k) Retirement Plan
Health Savings Account (HSA)
Disability Insurance (Short-Term and Long-Term)
Life and AD&D Insurance
Paid Sick Leave (where required by applicable state or local law)
Supplemental Insurance Plans
Identity Theft Protection
Pet Insurance
Employee Wellness Programs
Employee Assistance Program (EAP)
Career Growth and Professional Development Opportunities

Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws.

About Cynet Systems

Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia.

As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.

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More about this job

Responsibilities

Design and deploy generative AI solutions using large language models and diffusion models, applying prompt engineering, fine-tuning, and retrieval-augmented generation. Develop and scale machine learning pipelines, optimize model inference for speed, latency, and cost, and integrate AI models into production systems and enterprise workflows.

Requirements

Requires 8+ years of experience in data science or AI engineering, including 2+ years focused on generative AI, along with expertise in deep learning frameworks, AI development tools, machine learning methods, databases, MLOps, cloud platforms, and GPU acceleration. A master’s degree in computer science, data science, mathematics, or a related quantitative field is required.

Skills

Python
Generative AI
Large Language Models
Prompt Engineering
LLM Fine-Tuning
Retrieval-Augmented Generation
PyTorch
TensorFlow
JAX
Hugging Face
LangChain
LlamaIndex
vLLM
Machine Learning
Deep Learning
CUDA

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
401(k) Retirement Plan
Health Savings Account
Short-Term Disability Insurance
Long-Term Disability Insurance
Life and AD&D Insurance
Paid Sick Leave
Supplemental Insurance Plans
Identity Theft Protection
Pet Insurance
Employee Wellness Programs
Employee Assistance Program
Career Growth and Professional Development

Visa sponsorship

Not detected in the job text

Keywords

Generative AI
Large Language Models
Diffusion Models
Prompt Engineering
Fine-Tuning
Retrieval-Augmented Generation
Python
PyTorch
TensorFlow
JAX
Hugging Face
LangChain
LlamaIndex
vLLM
Machine Learning
Deep Learning
Regression
Clustering
Decision Trees
Ensemble Methods
Transformers
CNNs
RNNs
RLHF
Vector Databases
SQL
NoSQL
MLflow
Kubeflow
CUDA

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