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
- Posting language
- English
- Posted
Original job description
Job Overview
Pay Range: $50.00hr - $55.00hr
Requirement/Must Have
Our Benefits Include:
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.
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.
- 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.
- 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.
- Master s degree in Computer Science, Data Science, Mathematics, or a related quantitative field.
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
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.
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
Categories
- Technology
- Data & Analytics
- Software
- Science & Research
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