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Machine Learning Engineer - Job Opportunity at Sanofi

Toronto, Canada
Full-time
Mid-level
Posted: August 19, 2025
Hybrid
CAD 94,700-136,767 per year

Benefits

Comprehensive extended health care coverage providing superior medical protection beyond standard provincial healthcare
High-quality healthcare programs with prevention and wellness initiatives supporting long-term employee health
Thoughtfully designed rewards package that recognizes contributions and amplifies professional impact
Wide range of health and wellbeing benefits supporting both employee and family needs
International career mobility opportunities within a global organization spanning 100+ countries
World-class mentorship and training programs with renowned AI/ML leaders and academics

Key Responsibilities

Lead the design, construction, and maintenance of cloud-hosted AI/ML products with automated pipelines that strategically position Sanofi as an AI-first organization
Architect and implement automated ML pipelines for training and inference, directly contributing to accelerated drug discovery and patient outcomes
Drive lifecycle management of deployed AI/ML applications, ensuring continuous innovation delivery across R&D, manufacturing, and commercial operations
Serve as an intermediate-level MLOps subject matter expert, establishing enterprise standards that scale across Sanofi's global digital transformation
Build reusable processes and components that enable seamless ML operations, supporting the company's mission to bring life-saving treatments to market faster
Guide stakeholders and solution partners through complex AI solutions, influencing strategic decisions that impact millions of patients globally
Cultivate relationships with application users to develop educational content and communication strategies that drive adoption of AI innovations
Research and gain expertise on emerging technologies, positioning Sanofi at the forefront of pharmaceutical AI advancement

Requirements

Education

University degree (Bachelor, Master or PhD) in Computer Science, Information Systems, Software Engineering, or another relevant engineering discipline

Experience

Minimum 3 years of experience in building, deploying, monitoring and maintaining AI/ML applications utilizing cloud technologies

Required Skills

Python programming language MLOps technologies (Github, Argo, Metaflow, WandB, Snowflake) Cloud technologies (AWS, GCP, Azure, Snowflake) CI/CD pipelines for AI/ML driven app development Large scale data and ML pipelines Architecture decision records (ADRs) Agile team methodology Relational databases (Postgres SQL) Non-relational databases (Graph database, Vector Database) Visualization technologies (Python DASH, Tableau, PowerBI) Backend APIs (REST) Infrastructure as code tools (Docker, Kubernetes, Terraform) Excellent communication skills in English Structured, goal-oriented approach Fast-paced environment management Multiple priority management Interpersonal skills for technical leadership
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Sauge AI Market Intelligence

Industry Trends

The pharmaceutical industry is experiencing unprecedented digital transformation, with AI/ML becoming critical for drug discovery acceleration, reducing traditional 10-15 year development cycles by 30-50% through predictive modeling and automated analysis Healthcare companies are investing heavily in MLOps infrastructure, with the global MLOps market expected to grow from $1.5 billion in 2023 to $35 billion by 2030, driven by regulatory compliance needs and scalability requirements Major pharmaceutical companies are establishing dedicated AI factories and centers of excellence, creating significant demand for MLOps engineers who can bridge the gap between data science innovation and production-ready healthcare solutions Cloud-first AI strategies are becoming mandatory in pharmaceuticals, with companies migrating legacy systems to support real-time ML model deployment across global operations, research facilities, and manufacturing sites

Salary Evaluation

The salary range of CAD 94,700-136,767 is competitive for Toronto's market, positioning slightly above average for mid-level MLOps engineers. Comparable roles at tech companies typically range CAD 85,000-130,000, while pharmaceutical companies often offer 10-15% premiums due to regulatory complexity and specialized domain knowledge requirements.

Role Significance

Typically works within cross-functional agile pods of 6-8 members including data scientists, data engineers, and product managers, while collaborating with larger networks of 20-30 stakeholders across global R&D, manufacturing, and commercial teams.
This is a strategically important mid-level position with significant autonomy and influence over Sanofi's AI transformation. The role combines technical execution with thought leadership, requiring independent decision-making on architecture and standards that will impact global operations and patient outcomes.

Key Projects

Implementation of automated drug discovery pipelines that accelerate molecule identification and testing phases Development of manufacturing optimization models that improve vaccine production efficiency and quality control Creation of clinical trial prediction systems that enhance patient recruitment and outcome forecasting Building of supply chain intelligence platforms that ensure global medicine availability and distribution optimization

Success Factors

Deep understanding of pharmaceutical regulatory requirements (GxP, data privacy, SOX) combined with cutting-edge MLOps technical skills creates unique value proposition in healthcare AI market Ability to translate complex AI/ML concepts into business impact metrics that resonate with healthcare executives and regulatory stakeholders Strong collaboration skills across diverse global teams, cultural contexts, and technical backgrounds, essential for success in Sanofi's 100+ country organization Continuous learning mindset and adaptability to emerging technologies, crucial for staying ahead in the rapidly evolving intersection of AI and pharmaceutical innovation Results-oriented approach with focus on patient outcomes and life-saving impact, aligning technical work with Sanofi's mission-driven culture

Market Demand

Extremely high demand exists for MLOps engineers in pharmaceutical companies, with a critical shortage of professionals who understand both machine learning operations and healthcare regulatory environments. The convergence of AI adoption and regulatory compliance creates a premium market for these specialized skills.

Important Skills

Critical Skills

Python and MLOps technologies form the technical foundation for building and maintaining AI/ML pipelines that directly impact drug development timelines and patient outcomes. Proficiency in these tools is essential for implementing automated systems that can scale across Sanofi's global operations. Cloud platform expertise (AWS, GCP, Azure) is crucial for deploying AI solutions that meet pharmaceutical industry requirements for security, compliance, and global accessibility. Healthcare organizations require robust, scalable infrastructure that can handle sensitive patient data and regulatory scrutiny. CI/CD pipeline experience is vital for maintaining the continuous delivery of AI/ML models in a regulated environment where changes must be tracked, validated, and deployed systematically to ensure patient safety and regulatory compliance.

Beneficial Skills

Healthcare domain knowledge and understanding of pharmaceutical development processes would accelerate contribution to drug discovery and clinical trial optimization projects Advanced knowledge of compliance frameworks (GxP, SOX, data privacy regulations) would enhance value in the highly regulated pharmaceutical environment Experience with specialized healthcare AI applications such as molecular modeling, clinical trial design, or biomarker discovery would provide competitive advantage in Sanofi's core business areas Leadership and mentoring skills would support career progression toward management roles in Sanofi's expanding AI organization

Unique Aspects

Direct impact on life-saving drug discovery and vaccine development, providing meaningful work that contributes to global health outcomes and patient care
Access to world-class mentorship from renowned AI/ML leaders and academic experts, offering exceptional professional development opportunities
Exposure to cutting-edge healthcare AI applications including drug discovery, clinical trials, manufacturing optimization, and personalized medicine
Global career mobility across 100+ countries with opportunities to work on diverse therapeutic areas and healthcare challenges
Integration of AI/ML work with regulatory compliance and quality standards, providing unique expertise in healthcare-specific technical requirements

Career Growth

Career progression typically occurs within 2-4 years for high-performing individuals, accelerated by Sanofi's rapid digital transformation and global expansion of AI initiatives across multiple therapeutic areas and geographical markets.

Potential Next Roles

Senior MLOps Engineer or Lead ML Engineer within 2-3 years, taking on larger architectural decisions and team leadership responsibilities AI/ML Product Manager roles, leveraging technical expertise to drive product strategy and roadmap development Data Science Manager or AI Engineering Manager positions, leading teams of data scientists and ML engineers AI Strategy Consultant or Solutions Architect roles, designing enterprise-wide AI transformation initiatives

Company Overview

Sanofi

Sanofi is a Fortune 500 global pharmaceutical leader with €37+ billion in annual revenue, operating across 100+ countries with a workforce exceeding 100,000 employees. The company is undergoing a massive digital transformation, positioning itself as an AI-first organization with significant investments in data science, machine learning, and digital health technologies.

Sanofi ranks among the top 5 global pharmaceutical companies, competing with Pfizer, Roche, and Novartis, with particular strength in vaccines, rare diseases, and general medicines. The company's commitment to AI transformation represents a strategic differentiator in the highly competitive pharmaceutical landscape.
Toronto represents a key hub in Sanofi's North American operations, benefiting from Canada's strong AI research ecosystem, government support for healthcare innovation, and proximity to leading universities and tech talent. The Toronto office plays a crucial role in the company's global digital strategy.
Sanofi emphasizes mission-driven work with strong focus on patient impact, collaborative global teamwork, and scientific excellence. The culture balances pharmaceutical industry rigor and compliance requirements with startup-like innovation and agility in digital transformation initiatives.
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