EI
GEN AI Specialist
eTeam Inc.
Location not stated
1 month ago
- AI
- Machine Learning
- AI/ML
- Large Language Models
- RAG
- PyTorch
- TensorFlow
- JAX
- Hugging Face
- LangChain
- LlamaIndex
- vLLM
- Python
- CNNs
- RLHF
- Chroma
- Pinecone
- Milvus
- SQL
- NoSQL
- MLOps
- MLflow
- Kubeflow
- Triton
- AWS SageMaker
- Azure
- Azure AI
- GCP
- Vertex AI
- CUDA
1 month ago
Role Name: GEN AI Specialist
Location: Missisauga ON
JOB DESCRIPTION:
Job Description: GenAI & AI/ML Framework Specialist (C1/C2)
Role Overview:
We are seeking a GenAI & AI/ML Framework Specialist to design, build, and scale next-generation artificial intelligence solutions.
You will develop advanced machine learning algorithms, optimize open-source frameworks, and implement Generative AI architectures into enterprise applications.
Key Responsibilities
- GenAI & Model Development
- 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.
- Framework & Pipeline Engineering
- 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.
- Technical Skills Required
- AI/ML Frameworks & Libraries
- Core Frameworks: Deep expertise in PyTorch, TensorFlow, or JAX.
- GenAI Ecosystem: Hands-on experience with Hugging Face, LangChain, LlamaIndex, and vLLM.
- Core Languages: Mastery of Python for performance tuning.
- Algorithms & Math
- Machine Learning: Deep understanding of regression, clustering, decision trees, and ensemble methods.
- Deep Learning: Strong grasp of Transformers, CNNs, RNNs, and reinforcement learning (RLHF).
- Data Infrastructure: Experience with Vector Databases (ChromaDB, Pinecone, Milvus) and SQL/NoSQL.
- MLOps & Infrastructure
- Deployment: Experience with MLflow, Kubeflow, or Triton Inference Server.
- Cloud & Compute: Proficiency with AWS (SageMaker), Azure (Azure AI), or GCP (Vertex AI), alongside GPU acceleration (CUDA).
- Experience & Qualifications
- Experience: 8 years in data science or AI engineering, with 2 years dedicated to Generative AI.
- Education: Master’s in Computer Science, Data Science, Mathematics, or a related quantitative field.
GEN AI Specialist · eTeam Inc.