The role involves post-training of LLMs, model alignment, server operation for checkpoint routing, and building evaluation pipelines.
Job Responsibilities：
1. Advanced post-training of large language models (e.g. SFT, RLHF/RLAIF, continual pretraining).
2. Aligning models for reliable JSON-schema function calls and external tool usage.
3. Design, deploy, and operate Model Context Protocol (MCP) servers that handle checkpoint routing, manage context windows, and enforce safety gates.
4. Experience in distributed training and inference with DeepSpeed/FSDP, LoRA/QLoRA, mixed precision, and performance tuning on vLLM or Triton clusters.
5. Build offline and live eval pipelines for alignment, factuality, grounding, and hallucinations.
Qualifications
1. Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
2. 3+ years of experience in developing and optimizing large language models.
3. Proven track record in implementing advanced post-training techniques (SFT, RLHF, RLAIF, continual pretraining).
4. Hands-on experience with distributed training frameworks (DeepSpeed, FSDP) and optimization techniques (LoRA, QLoRA, mixed precision).
5. Familiarity with model alignment, JSON-schema function calls, and external tool integration.
6. Experience in building and maintaining evaluation pipelines for model performance assessment.
7. Proficiency in Python and relevant machine learning frameworks (e.g., PyTorch, TensorFlow).
8. Strong understanding of distributed systems and high-performance computing.
9. Experience with model deployment and inference optimization on vLLM or Triton clusters.
10. Knowledge of JSON-schema and API development.
Top Skills
Deepspeed
Fsdp
Lora
Python
PyTorch
Qlora
TensorFlow
Triton
Vllm
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What you need to know about the Montreal Tech Scene
With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.
Key Facts About Montreal Tech
- Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
- Major Tech Employers: SAP, Google, Microsoft, Cisco
- Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
- Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
- Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
- Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal
