Senior Machine Learning Engineer

November 15 2024
Industries Consulting services
Categories Data analyst, BI, Mining, AI,
Remote
Toronto, ON • Full time

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.

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 streamlined, automated pipeline for transitioning ML models from development to production.
  • Design, Develop and maintain processes for model versioning, training, deployment, and continuous updates.
  • Implement best practices for model monitoring, performance evaluation, and drift detection.
  • Design and build scalable, reproducible infrastructure for ML development and deployment.
  • Implement infrastructure as code (IaC) principles to ensure consistent and reliable 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, data quality, and system health.
  • Troubleshoot and optimize ML pipelines for improved efficiency, reliability, and scalability.
  • Implement robust security controls and access management 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.
  • Lead and mentor a team of junior MLOps Engineers, fostering their growth and skill development.
  • Provide technical guidance on MLOps frameworks, deployment strategies, and observability best practices.
  • Cultivate a culture of continuous learning, innovation, and knowledge sharing within the team.
  • Work closely with business stakeholders to understand ML project objectives and requirements.
  • Communicate effectively with project managers, and cross-functional teams.
  • Provide regular updates on project progress, performance, and any issues or risks.

What You'll Bring?

  • 3 to 5 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.
  • Bachelor's degree in computer science, Data Science, Information Technology, or a related field.
  • Proficiency in Python, SQL, and relevant ML libraries (e.g., TensorFlow, PyTorch).
  • Familiarity with cloud platforms (e.g., GCP, AWS) and containerization (Docker, Kubernetes).
  • Strong problem-solving skills and ability to work in a collaborative environment.
  • Expertise in software development methodologies, such as Agile, DevOps, and CI/CD.
  • Proficiency in programming languages, including Python and R.
  • Excellent communication and stakeholder management skills.

Additional Skills:

  • Preferred certifications in cloud platforms (e.g., AWS, Azure, GCP) and MLOps.
  • Azure synapse experience preferred

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

Apply now!

Similar offers

Searching...
No similar offer found.
An error has occured, try again later.

Jobs.ca network