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Machine Learning Engineer

AT ZS
ZS

Machine Learning Engineer

Toronto, Canada

Minimum Salary: $70,000.00 - $79,000.00

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, our most valuable asset is our people. Here you'll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning; bold ideas; courage and passion to drive life-changing impact to ZS.

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Our most valuable asset is our people.

At ZS we honor the visible and invisible elements of our identities, personal experiences and belief systems-the ones that comprise us as individuals, shape who we are and

make us unique. We believe your personal interests, identities, and desire to learn are part of your success here. Learn more about our diversity, equity, and inclusion efforts and the networks ZS supports to assist our ZSers in cultivating community spaces, obtaining the resources they need to thrive, and sharing the messages they are passionate about.

What You'll Do?

  • Collaborate with data science teams to create a seamless pipeline for transitioning ML models from development to production.
  • Develop and maintain automated processes for model creation, training, deployment, and updates.
  • Implement best practices for model versioning, monitoring, and automated deployment.
  • Develop and maintain scalable infrastructure for ML development and deployment initiatives.
  • Implement infrastructure as code (IaC) principles to ensure reproducible ML environments.
  • Integrate ML pipelines into continuous integration and continuous deployment (CI/CD) workflows.
  • Ensure reliable and efficient deployment of ML models into production environments.
  • Implement monitoring solutions to track model performance, detect data drift, and ensure data quality.
  • Troubleshoot and optimize ML pipelines for maximum efficiency and reliability.
  • Implement robust security controls and safeguards for ML systems.
  • Ensure compliance with industry standards (e.g., GDPR, HIPAA) during model deployment.
  • Collaborate with legal and compliance teams to address regulatory requirements.
  • Work closely with data science teams to understand project objectives and translate them into engineering solutions.
  • Communicate effectively with stakeholders, including project managers, and cross-functional teams.

What You'll Need?

  • Bachelor's or master's degree in computer science, Data Science, or a related technical field.
  • Proficiency in Python, SQL, and relevant ML libraries (e.g., TensorFlow, PyTorch).
  • Expertise in cloud platforms (e.g., GCP, AWS) and containerization (Docker, Kubernetes).
  • Strong problem-solving skills and ability to work in a collaborative environment.
  • Familiarity with software development methodologies, such as Agile, DevOps, and CI/CD.
  • Proficiency in programming languages, including Python and R.
  • Experience with software development life cycle.
  • 1-3 years of hands-on experience in cloud engineering, infrastructure, or related roles.
  • Minimum of 4 years of professional experience in MLOps, machine learning, and DevOps.

Additional skills:

  • Experince with Azure Synapse is preferred
  • Preferred certifications in cloud platforms (e.g., AWS, Azure, GCP) and MLOps

Perks & Benefits:

ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth and professional development. Our robust skills development programs, multiple career progression options and internal mobility paths and collaborative culture empowers you to thrive as an individual and global team member.

We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections.

Considering applying?

At ZS, we're building a diverse and inclusive company where people bring their passions to inspire life-changing impact and deliver better outcomes for all. We are most interested in finding the best candidate for the job and recognize the value that candidates with all backgrounds, including non-traditional ones, bring. If you are interested in joining us, we encourage you to apply even if you don't meet 100% of the requirements listed above.

To Complete Your Application:

Candidates must possess work authorization for their intended country of employment.

An on-line application, including a full set of transcripts (official or unofficial), is required

to be considered.

NO AGENCY CALLS, PLEASE.

Find Out More At:

www.zs.com

Client-provided location(s): Toronto, ON, Canada
Job ID: ZS-21561
Employment Type: Full Time

Perks and Benefits

  • Health and Wellness

    • Health Insurance
    • Dental Insurance
    • Vision Insurance
    • Life Insurance
    • Short-Term Disability
    • Long-Term Disability
    • FSA
    • Mental Health Benefits
  • Parental Benefits

    • Birth Parent or Maternity Leave
    • Non-Birth Parent or Paternity Leave
    • Fertility Benefits
    • Family Support Resources
    • Adoption Leave
  • Work Flexibility

    • Flexible Work Hours
    • Hybrid Work Opportunities
  • Office Life and Perks

    • Happy Hours
    • Snacks
    • Some Meals Provided
    • Company Outings
    • On-Site Cafeteria
    • Holiday Events
    • Commuter Benefits Program
  • Vacation and Time Off

    • Paid Vacation
    • Paid Holidays
    • Personal/Sick Days
    • Volunteer Time Off
  • Financial and Retirement

    • 401(K)
    • 401(K) With Company Matching
    • Performance Bonus
    • Relocation Assistance
  • Professional Development

    • Tuition Reimbursement
    • Learning and Development Stipend
    • Promote From Within
    • Mentor Program
    • Shadowing Opportunities
    • Access to Online Courses
    • Lunch and Learns
    • Work Visa Sponsorship
    • Leadership Training Program
  • Diversity and Inclusion

    • Diversity, Equity, and Inclusion Program
    • Employee Resource Groups (ERG)