📍 Job Overview

Job Title: Senior DevOps Engineer
Company: Deep Genomics
Location: Toronto, Ontario, Canada
Job Type: Full-time
Category: DevOps Engineer
Date Posted: 2025-06-20
Experience Level: 5-10 years
Remote Status: Hybrid (Toronto & Cambridge, MA)

🚀 Role Summary

Key Responsibilities: Manage infrastructure for software, data, and ML platforms, both in the cloud and on-premises. Collaborate closely with engineering, security, and compliance teams to implement and promote DevSecOps principles across the organization.
Key Technologies: Infrastructure as Code (Terraform, Helm), Containerization (Docker, Kubernetes), CI/CD, Python, Shell Scripting, Automation, Machine Learning, Hybrid-Cloud Architectures, Security Best Practices, Secrets Management, Observability.

📝 Enhancement Note: This role requires a strong background in DevOps and MLOps, with a focus on managing complex infrastructure for machine learning workloads. Proficiency in cloud environments and experience with modern ML platforms are essential for success in this role.

💻 Primary Responsibilities

Infrastructure Management: Manage infrastructure for software, data, and ML platforms, both in the cloud and on-premises GPU clusters. Ensure seamless development of sophisticated ML models, software applications, and data pipelines.
Integration Design: Design and implement integrations between infrastructure components to ensure seamless flow of data in a robust, reliable, and secure manner.
Automation & Streamlining: Streamline and/or automate operational tasks such as infrastructure provisioning, configuration management, and application deployment to improve efficiency and reduce manual effort.
Monitoring & Alerting: Implement and manage robust monitoring, logging, and alerting for key infrastructure components to ensure system health and quick issue resolution.
Collaboration & DevSecOps: Collaborate closely with engineering, security, and compliance teams to implement and promote DevSecOps principles across the organization, ensuring secure and compliant infrastructure.

📝 Enhancement Note: This role requires a strong focus on collaboration and communication, working closely with various teams to ensure infrastructure meets the needs of diverse scientific and engineering teams. Experience with mentoring and elevating other team members' skills is highly valued.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Engineering, or a related field. Relevant experience may be considered in lieu of a degree.

Experience: 5+ years of experience working as a DevOps/MLOps engineer, SRE, or infrastructure engineer.

Required Skills:

Proficiency in Infrastructure as Code tools (e.g., Terraform and Helm) in public cloud environments.
Deep expertise in containerization and orchestration technologies like Docker and Kubernetes.
Strong understanding of identity management and security best practices.
Extensive experience designing, implementing, and maintaining CI/CD pipelines (e.g., CircleCI).
Demonstrated experience with mentoring and elevating other team members' skills to adhere to DevOps best practices.

Preferred Skills:

Experience with Python/Shell scripting and automation tools.
Hands-on experience with modern ML platforms and frameworks (e.g., Weights & Biases, Metaflow, MLflow, Ray) and familiarity with the operational challenges of scaling ML workloads.
Experience designing and operating hybrid-cloud architectures that span on-premises and cloud environments, with an emphasis on resilience, observability, and cost optimization.
Familiarity with secrets management, zero-trust architectures, and secure-by-default design patterns in regulated or privacy-sensitive environments.

📝 Enhancement Note: This role requires a strong foundation in DevOps principles and experience with modern ML platforms. Familiarity with hybrid-cloud architectures and secure-by-default design patterns is highly desirable.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate experience managing complex infrastructure for software, data, and ML platforms.
Showcase successful integrations between infrastructure components, ensuring seamless data flow.
Highlight automation and streamlining efforts that improved efficiency and reduced manual effort.
Display robust monitoring, logging, and alerting implementations for key infrastructure components.

Technical Documentation:

Provide detailed documentation of infrastructure components, including configuration management and deployment processes.
Include system diagrams and architecture overviews to illustrate infrastructure design and complexity.
Demonstrate understanding of security best practices and compliance requirements through relevant documentation.

📝 Enhancement Note: This role requires a strong focus on documentation and knowledge sharing. Portfolio should demonstrate clear and concise technical documentation that enables easy onboarding and collaboration.

💵 Compensation & Benefits

Salary Range: CAD 120,000 - CAD 160,000 per year (based on regional market research and experience level)

Benefits:

Health Coverage (Medical, Dental, Vision)
Employee Assistance Program
Flexible Hours & Extended Long Weekends
Holiday Shutdown & Unlimited Personal Days
Maternity & Parental Leave Top-Up
Learning and Development Budget & Lunch and Learns

Working Hours: Full-time position with standard business hours, plus on-call rotations for infrastructure management and support.

📝 Enhancement Note: The salary range provided is an estimate based on regional market research and experience level. Deep Genomics offers a highly competitive compensation package, including meaningful stock ownership.

🎯 Team & Company Context

🏢 Company Culture

Industry: Biotechnology & Life Sciences

Company Size: Medium (150-250 employees)

Founded: 2015

Team Structure:

The DevOps team at Deep Genomics consists of 5-10 engineers, working closely with software engineering, machine learning, and biology teams.
The team follows an Agile/Scrum methodology, with regular sprint planning and code reviews.
Cross-functional collaboration is encouraged, with a focus on knowledge sharing and continuous learning.

Development Methodology:

Agile/Scrum methodologies are used for sprint planning and code reviews.
Infrastructure as Code (IaC) principles are followed for version control, deployment, and configuration management.
CI/CD pipelines are implemented to automate deployment and ensure consistent, reliable releases.

Company Website: deepgenomics.com

📝 Enhancement Note: Deep Genomics values collaboration, innovation, and continuous learning. The company fosters a culture of knowledge sharing and encourages employees to push the boundaries of drug discovery through thoughtfully engineered systems.

📈 Career & Growth Analysis

Web Technology Career Level: Senior DevOps Engineer

Reporting Structure: This role reports directly to the Director of Engineering and collaborates closely with various teams, including software engineering, machine learning, and biology.

Technical Impact: The Senior DevOps Engineer plays a crucial role in enabling seamless development of sophisticated ML models, software applications, and data pipelines. Their work directly impacts the efficiency and effectiveness of the entire organization.

Growth Opportunities:

Technical Growth: Deepen expertise in infrastructure management, hybrid-cloud architectures, and MLOps. Explore emerging technologies and contribute to open-source projects.
Leadership Growth: Mentor junior team members and contribute to the development of DevOps best practices across the organization. Grow into a technical leadership role, driving infrastructure strategy and roadmap.
Career Progression: Transition into a more specialized role, such as Site Reliability Engineer (SRE) or Infrastructure Architect, or move into a management role, such as Engineering Manager or Director of Engineering.

📝 Enhancement Note: Deep Genomics offers significant growth opportunities for motivated and talented individuals. The company values internal promotions and encourages employees to develop their skills and advance their careers within the organization.

🌐 Work Environment

Office Type: Hybrid (Toronto & Cambridge, MA)

Office Location(s):

Toronto, Ontario, Canada: 240 Richmond St W, Toronto, ON M5H 3C2
Cambridge, Massachusetts, United States: 200 Technology Square, Cambridge, MA 02139

Workspace Context:

The Toronto office is located in the heart of the city, with easy access to public transportation and numerous amenities.
The Cambridge office is situated in Kendall Square, a global center of biotechnology and life sciences.
Both offices offer collaborative workspaces, with multiple monitors and testing devices available for engineers.

Work Schedule: Standard business hours, plus on-call rotations for infrastructure management and support. Flexible work arrangements are available, with a focus on results and productivity.

📝 Enhancement Note: Deep Genomics offers a flexible and collaborative work environment, with a focus on results and productivity. The company values work-life balance and provides numerous benefits to support employee well-being.

📄 Application & Technical Interview Process

Interview Process:

Phone Screen: A brief call to discuss your background, experience, and motivation for the role (30 minutes).
Technical Deep Dive: A detailed discussion of your technical skills, experience, and portfolio. Expect questions on infrastructure management, CI/CD pipelines, and hybrid-cloud architectures (60 minutes).
Behavioral & Cultural Fit: An assessment of your problem-solving skills, communication, and cultural fit with the team (30 minutes).
Final Interview: A meeting with the hiring manager and/or other senior team members to discuss your fit for the role and the company (30 minutes).

Portfolio Review Tips:

Highlight your experience managing complex infrastructure for software, data, and ML platforms.
Showcase successful integrations between infrastructure components and automation efforts that improved efficiency.
Demonstrate robust monitoring, logging, and alerting implementations for key infrastructure components.
Include clear and concise technical documentation that enables easy onboarding and collaboration.

Technical Challenge Preparation:

Brush up on your knowledge of Infrastructure as Code tools (e.g., Terraform and Helm) and containerization technologies (e.g., Docker and Kubernetes).
Familiarize yourself with modern ML platforms and frameworks (e.g., Weights & Biases, Metaflow, MLflow, Ray) and the operational challenges of scaling ML workloads.
Prepare for questions on hybrid-cloud architectures, security best practices, and secrets management.

ATS Keywords: Infrastructure as Code, Terraform, Helm, Docker, Kubernetes, CI/CD, Python, Shell Scripting, Automation, Machine Learning, Hybrid-Cloud Architectures, Security Best Practices, Secrets Management, Observability, Agile/Scrum, DevSecOps, MLOps, SRE, Infrastructure Architect, Engineering Manager, Director of Engineering.

📝 Enhancement Note: The interview process at Deep Genomics is designed to assess your technical skills, problem-solving abilities, and cultural fit with the team. Be prepared to discuss your experience and portfolio in detail and demonstrate your understanding of DevOps best practices and MLOps challenges.

🛠 Technology Stack & Web Infrastructure

Infrastructure as Code (IaC) Tools:

Terraform (Version Control, Deployment, Configuration Management)
Helm (Package Manager for Kubernetes)

Containerization & Orchestration Technologies:

Docker (Containerization)
Kubernetes (Orchestration)

CI/CD Pipelines:

CircleCI (Automated Deployment, Testing, and Release Management)

Monitoring & Logging Tools:

Prometheus (Monitoring)
ELK Stack (Logging, Search, and Analytics)

Cloud Platforms:

Amazon Web Services (AWS)
Google Cloud Platform (GCP)

On-Premises Infrastructure:

GPU Clusters (Machine Learning Workloads)

📝 Enhancement Note: Deep Genomics uses a combination of cloud and on-premises infrastructure to support its machine learning workloads. Familiarity with AWS, GCP, and on-premises GPU clusters is highly desirable.

👥 Team Culture & Values

DevOps Values:

Collaboration: Work closely with various teams to ensure infrastructure meets the needs of diverse scientific and engineering teams.
Innovation: Push the boundaries of drug discovery through thoughtfully engineered systems.
Continuous Learning: Stay up-to-date with emerging technologies and best practices in DevOps and MLOps.
Security: Implement and promote DevSecOps principles across the organization to ensure secure and compliant infrastructure.

Collaboration Style:

Cross-Functional Integration: Collaborate closely with software engineering, machine learning, and biology teams to ensure infrastructure meets their needs.
Code Review Culture: Participate in code reviews and pair programming to ensure high-quality infrastructure and knowledge sharing.
Knowledge Sharing: Contribute to the development of DevOps best practices and mentoring opportunities across the organization.

📝 Enhancement Note: Deep Genomics values collaboration, innovation, and continuous learning. The company fosters a culture of knowledge sharing and encourages employees to push the boundaries of drug discovery through thoughtfully engineered systems.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Scaling ML Workloads: Design and implement infrastructure that can scale to support the growing demands of machine learning workloads.
Hybrid-Cloud Architecture: Design and operate hybrid-cloud architectures that span on-premises and cloud environments, with an emphasis on resilience, observability, and cost optimization.
Secure-by-Default Design Patterns: Implement secrets management, zero-trust architectures, and secure-by-default design patterns in regulated or privacy-sensitive environments.

Learning & Development Opportunities:

Technical Skill Development: Deepen expertise in infrastructure management, hybrid-cloud architectures, and MLOps. Explore emerging technologies and contribute to open-source projects.
Conference Attendance & Certification: Attend industry conferences, obtain relevant certifications, and engage with the local tech community to stay up-to-date with emerging trends and best practices.
Technical Mentorship & Leadership Development: Mentor junior team members and contribute to the development of DevOps best practices across the organization. Grow into a technical leadership role, driving infrastructure strategy and roadmap.

📝 Enhancement Note: Deep Genomics offers significant technical challenges and growth opportunities for motivated and talented individuals. The company values continuous learning and encourages employees to develop their skills and advance their careers within the organization.

💡 Interview Preparation

Technical Questions:

Infrastructure Management: Describe your experience managing complex infrastructure for software, data, and ML platforms. How have you ensured seamless development and scalability?
CI/CD Pipelines: Explain your experience designing, implementing, and maintaining CI/CD pipelines. How have you optimized deployment, testing, and release management?
Hybrid-Cloud Architectures: Discuss your experience designing and operating hybrid-cloud architectures. How have you ensured resilience, observability, and cost optimization?
Security Best Practices: Explain your understanding of security best practices and how you have implemented them in your previous roles. How do you ensure secure and compliant infrastructure?

Company & Culture Questions:

Company Culture: Describe what attracts you to Deep Genomics' company culture and how you think you would fit in with the team.
DevSecOps Principles: Explain your understanding of DevSecOps principles and how you have implemented them in your previous roles. How do you ensure secure and compliant infrastructure while maintaining agility and innovation?
Machine Learning Impact: Describe how you have enabled seamless development of sophisticated ML models, software applications, and data pipelines in your previous roles. How do you ensure infrastructure meets the needs of diverse scientific and engineering teams?

Portfolio Presentation Strategy:

Live Demonstration: Prepare a live demonstration of your portfolio, showcasing your experience managing complex infrastructure for software, data, and ML platforms.
Technical Walkthrough: Include a detailed technical walkthrough of your infrastructure components, integrations, and automation efforts.
User Experience & Collaboration: Highlight your ability to work closely with various teams and ensure infrastructure meets their needs. Demonstrate your understanding of user experience and collaboration principles in a DevOps context.

📝 Enhancement Note: The interview process at Deep Genomics is designed to assess your technical skills, problem-solving abilities, and cultural fit with the team. Be prepared to discuss your experience and portfolio in detail and demonstrate your understanding of DevOps best practices and MLOps challenges.

📌 Application Steps

To apply for this Senior DevOps Engineer position at Deep Genomics:

Submit Your Application: Click the "Apply" button on the job listing and follow the prompts to submit your resume and any relevant portfolio links.
Customize Your Portfolio: Tailor your portfolio to highlight your experience managing complex infrastructure for software, data, and ML platforms. Include live demos and responsive examples that demonstrate your technical skills and problem-solving abilities.
Optimize Your Resume: Highlight your relevant experience, skills, and achievements in your resume. Use web development and server administration-relevant keywords to improve search visibility and match with the job description.
Prepare for Technical Interview: Brush up on your knowledge of Infrastructure as Code tools, containerization technologies, and modern ML platforms. Familiarize yourself with hybrid-cloud architectures, security best practices, and secrets management. Review the company's technology stack and be prepared to discuss your experience and portfolio in detail.
Research the Company: Learn about Deep Genomics' mission, values, and culture. Understand their approach to drug discovery, machine learning, and biotechnology. Be prepared to discuss how your skills and experience align with the company's goals and objectives.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web development/server administration industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Senior DevOps Engineer