Closed listing
Research Developer, Frontier AI Incubation, DeepMind
- Montreal, QC, Canada
Full-time
This opening has closed.
The original listing is kept below for reference.
Job details
- Job type
- Full-time
- Closing date
- Posting language
- English
- Posted
Similar jobs hiring now
Search current openingsOriginal job description
Archived listing. The details below describe a past opening.
This posting is for an existing vacancy.
Google utilizes AI tools to assist in assessing candidates in our hiring processes.
Minimum qualifications:
At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.
Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Canada: $185000 - $190000 (CAD) + 15% bonus target + equity + benefits
Responsibilities
Learn more about benefits at Google .
Google utilizes AI tools to assist in assessing candidates in our hiring processes.
Minimum qualifications:
- Bachelor's degree in Computer Science, Machine Learning, Mathematics, Statistics, or equivalent practical experience.
- 2 years of experience in machine learning, algorithm design, data structures, or distributed software systems.
- 2 years of experience programming in Python or C++.
- 1 year of experience taking technical projects or machine learning systems from conceptual formulation to implementation and deployment.
- Experience developing, fine-tuning, or optimizing foundation models including techniques such as reinforcement learning from human/AI feedback, supervised fine-tuning, parameter-efficient tuning, or inference optimization.
- Experience or interest in personalization, adaptive systems, user modeling, retrieval-augmented generation, or agentic memory architectures.
- Experience with machine learning frameworks and large-scale model training or serving infrastructure.
- Experience collaborating across research and product boundaries to co-design technical architectures.
- Experience in scientific analysis, technical problem-solving, and technical communication.
At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.
Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Canada: $185000 - $190000 (CAD) + 15% bonus target + equity + benefits
Responsibilities
Learn more about benefits at Google .
- Design, train, and optimize foundational algorithms and ML systems (e.g., personalized model adaptation, agentic workflows, contextual memory architectures, dynamic prompt optimization, and multimodal reasoning).
- Lead end-to-end technical development from algorithmic design and experimental prototyping to production-grade architecture and scaled serving infrastructure.
- Partner directly with Google development and product teams to integrate and harden our core technologies within production environments (e.g., Project Helix, agent workspaces, and intelligent system integrations).
- Formulate novel automated and human-in-the-loop evaluation methodologies to measure capability gains, latency/compute efficiency, alignment, and personalization fidelity.
More about this job
Responsibilities
Design, train, and optimize foundational algorithms and ML systems, including agentic workflows and multimodal reasoning. Lead end-to-end technical development from prototyping to production-grade architecture and scaled serving infrastructure.
Requirements
Requires a Bachelor's degree in Computer Science or a related field with at least 2 years of experience in ML, algorithm design, and Python or C++. Candidates should have experience taking ML systems from conceptual formulation to deployment.
Skills
- Machine Learning
- Algorithm Design
- Data Structures
- Distributed Software Systems
- Python
- C++
- Foundation Models
- Reinforcement Learning
- Supervised Fine-Tuning
- Parameter-Efficient Tuning
- Inference Optimization
- Retrieval-Augmented Generation
- Agentic Memory Architectures
- ML Frameworks
- Large-Scale Model Training
- Technical Communication
Benefits
- Bonus target
- Equity
- Benefits
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Science & Research
- Engineering
- Data & Analytics
Keywords
- Frontier AI
- DeepMind
- Machine Learning
- Python
- C++
- Foundation Models
- RLHF
- SFT
- Inference Optimization
- RAG
- Agentic Workflows
- Multimodal Reasoning
- Distributed Systems
- Model Serving
- Algorithm Design
- Data Structures
- Personalization
- Adaptive Systems
- User Modeling
- Contextual Memory
- Prompt Optimization
- Project Helix
- Scientific Analysis
- Technical Architecture
- Production-Grade Infrastructure