AI Engineer Toronto (Hybrid In-Person Interview Required)
Machine Learning Deep Learning Generative AI NLP LLM Systems MLOps
Location: Toronto (Hybrid)
Employment: Full-Time
Experience: 5 years required
Interview: In-person required
Responsibilities / Requirements
- 5 years of experience in Machine Learning Deep Learning or AI Engineering
- Strong hands-on experience with Generative AI and modern ML techniques
- Deep understanding of NLP embeddings and information extraction methods
- Experience building and deploying production ML systems (MLOps)
- Strong knowledge of model training fine-tuning and inference optimization
- Solid foundation in algorithms data structures and system design
- Experience working with distributed computing frameworks
- Ability to lead technical execution in AI-driven initiatives
Nice to have
- Experience with LLM orchestration and agent-based systems
- Exposure to AI evaluation observability and monitoring tools
- Experience working with cloud-based AI infrastructure
Required Skills:
5 years of experience in Machine Learning Deep Learning or AI Engineering Strong hands-on experience with Generative AI and modern ML techniques Deep understanding of NLP embeddings and information extraction methods
Required Education:
any graduate
AI Engineer Toronto (Hybrid In-Person Interview Required) Machine Learning Deep Learning Generative AI NLP LLM Systems MLOpsLocation: Toronto (Hybrid) Employment: Full-Time Experience: 5 years required Interview: In-person requiredResponsibilities / Requirements5 years of experience in Machine...
AI Engineer Toronto (Hybrid In-Person Interview Required)
Machine Learning Deep Learning Generative AI NLP LLM Systems MLOps
Location: Toronto (Hybrid)
Employment: Full-Time
Experience: 5 years required
Interview: In-person required
Responsibilities / Requirements
- 5 years of experience in Machine Learning Deep Learning or AI Engineering
- Strong hands-on experience with Generative AI and modern ML techniques
- Deep understanding of NLP embeddings and information extraction methods
- Experience building and deploying production ML systems (MLOps)
- Strong knowledge of model training fine-tuning and inference optimization
- Solid foundation in algorithms data structures and system design
- Experience working with distributed computing frameworks
- Ability to lead technical execution in AI-driven initiatives
Nice to have
- Experience with LLM orchestration and agent-based systems
- Exposure to AI evaluation observability and monitoring tools
- Experience working with cloud-based AI infrastructure
Required Skills:
5 years of experience in Machine Learning Deep Learning or AI Engineering Strong hands-on experience with Generative AI and modern ML techniques Deep understanding of NLP embeddings and information extraction methods
Required Education:
any graduate
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