Senior MLOps & Cloud Infrastructure Engineer responsible for building, operating, and evolving the cloud infrastructure and engineering platforms behind production AI systems.
Responsibilities
Design, provision, and operate scalable infrastructure on GCP
Manage containerised applications and ML workloads with Kubernetes
Build reproducible infrastructure using Terraform
Design and improve CI/CD pipelines for backend services and data pipelines
Improve service availability, resilience, and incident response
Senior ML Engineer to build customer-facing AI platform and deliver production ML systems
Compensation
For this position, our hiring range for base annual pay is estimated to be CAD $160-200k at the time of this posting
Responsibilities
Take customer problems from idea to working prototype quickly, prove or kill an approach with data, and move what works into production
Train, fine-tune, and evaluate models for matching, classification, and extraction problems
Design and ship RAG systems, embedding-based retrieval, and LLM-powered features on AWS
Own the full ML lifecycle: experiment tracking, model versioning, deployment, monitoring, and retraining
Build evaluation that tells us whether something works: labeled golden sets, offline metrics (precision, recall), LLM-as-judge where it fits, and shadow or A/B testing before rollout
Lead design and delivery of Data Science and AI solutions across global operations, mentor junior talent, and translate insights into measurable business outcomes.
Responsibilities
Partner with business leaders to identify high-value opportunities
Collaborate with domain experts, business analysts, data engineers, software engineers, and integration teams
Lead cross-business-unit and global data science initiatives
Develop and validate machine learning models
Deploy and maintain production-ready models and AI applications
Requirements
Degree in a quantitative discipline such as Computer Science, Engineering, Statistics, or Mathematics
Nice to have: Knowledge of sales, manufacturing operations, supply chain, ERP systems, or finance
Develop and advance machine learning methods that learn from and reason across complex biomedical, clinical, molecular, and scientific data.
Compensation
The annual base salary for this position ranges from $106,000.00 to $176,600.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 15.0% of the base salary and eligibility to participate in our share based long term incentive program.
Responsibilities
Develop frontier AI methods for biomedical research
Design and execute rigorous experiments
Set the evaluation standard at scale
Translate models into scientific evidence
Build shared foundation
Requirements
PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, Computational Biology or related quantitative field
Master's degree with 2+ years of relevant industry or research experience
Nice to have: Experience applying AI in life sciences, biotechnology, healthcare, pharmaceuticals, or biomedical research
Nice to have: Experience with biological, molecular, imaging, clinical, or real-world health data
Nice to have: Experience building foundation models or multimodal learning systems for scientific applications
Lead advanced AI research to accelerate drug discovery and development at Pfizer.
Compensation
The annual base salary for this position ranges from $139,100.00 to $231,900.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 17.5% of the base salary and eligibility to participate in our share based long term incentive program.
Responsibilities
Develop frontier AI methods for biomedical research
Design and execute rigorous experiments
Set evaluation standards at scale
Translate models into scientific evidence
Build shared foundations
Requirements
PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, Computational Biology or related field
Master's degree with 5+ years of relevant industry or research experience
Nice to have: Experience applying AI in life sciences, biotechnology, healthcare, pharmaceuticals, or biomedical research
Nice to have: Experience with biological, molecular, imaging, clinical, or real-world health data
Nice to have: Experience building foundation models or multimodal learning systems for scientific applications
Develop and advance machine learning methods that learn from and reason across complex biomedical, clinical, molecular, and scientific data.
Compensation
The annual base salary for this position ranges from $106,000.00 to $176,600.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 15.0% of the base salary and eligibility to participate in our share based long term incentive program.
Responsibilities
Develop frontier AI methods for biomedical research
Design and execute rigorous experiments
Set the evaluation standard at scale
Translate models into scientific evidence
Build the shared foundation
Requirements
PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, Computational Biology or related quantitative field
Master's degree with 2+ years of relevant industry or research experience
Nice to have: Experience applying AI in life sciences, biotechnology, healthcare, pharmaceuticals, or biomedical research
Nice to have: Experience with biological, molecular, imaging, clinical, or real-world health data
Nice to have: Experience building foundation models or multimodal learning systems for scientific applications
This role is focused on ML engineering and MLOps execution, including pipeline development, model evaluation automation, and data / model lineage. It is not primarily a research or advanced modeling role.
Responsibilities
Build and maintain reproducible ML pipelines for Computer Vision and GenAI use cases
Convert notebook-based or ad hoc workflows into version-controlled, testable, and maintainable pipeline components
Standardize training, evaluation, and monitoring workflows across projects
Improve data validation, artifact management, and handoff between data preparation, model inference, and downstream delivery
Build and maintain CI/CD workflows for ML code, including automated testing and containerization
Lead machine learning engineering for AI safety evaluations, designing benchmarks, metrics, and tools to assess multimodal large language models.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
Responsibilities
Design and maintain safety benchmarks for large language and multimodal models
Define metrics and protocols that assess safety alongside model usefulness
Build reusable Python pipelines with versioned datasets and experiment tracking
Develop tools for automated red-teaming and failure mode discovery
Investigate model failures and develop regression tests
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