Lead Machine Learning Engineer
TLDR
Lead end-to-end production ML initiatives, architect scalable systems, mentor engineers, and drive innovative ML solutions for high-impact projects.
- Lead the design and development of scalable machine learning systems and end-to-end ML pipelines, ensuring reliability, performance, and maintainability in production environments.
- Define technical strategy for ML initiatives, contributing to architectural decisions, program inception, and alignment with broader business and client objectives.
- Own the full lifecycle of ML solutions, including model development, deployment, monitoring, evaluation, and iterative improvement based on real-world performance.
- Translate complex client requirements into feasible ML system designs, guiding delivery across distributed, high-stakes projects.
- Drive adoption of MLOps best practices, CI/CD for ML, and modern distributed system patterns across teams.
- Mentor and guide engineers through technical leadership, code reviews, and knowledge sharing, fostering a culture of excellence and continuous improvement.
- Stay current with emerging ML technologies and methodologies, proactively introducing innovations that enhance system capability and impact.
- 10+ years of software engineering experience with strong exposure to machine learning engineering, data science, and production-scale systems.
- Proven experience designing and operating scalable ML systems using frameworks such as Scikit-learn, TensorFlow, PyTorch, and MLFlow or Kubeflow.
- Strong proficiency in Python with expertise in writing clean, maintainable, and testable code.
- Deep understanding of distributed systems, cloud infrastructure (AWS, GCP, Azure), and infrastructure-as-code for ML workloads.
- Hands-on experience building ML pipelines, model training and deployment workflows, and implementing MLOps and CI/CD practices.
- Strong architectural thinking, including system design, scalability patterns, and lifecycle management of ML models.
- Excellent communication and stakeholder management skills, with the ability to influence technical and non-technical audiences.
- Demonstrated leadership ability, including mentoring engineers and driving technical direction in ambiguous environments.
- Experience working with modern ML infrastructure and tools for training, serving, monitoring, and evaluation.
- Competitive salary range aligned with Canadian market benchmarks ($156,000 – $251,000 CAD)
- Equity opportunities as part of a long-term incentive package
- Comprehensive health, dental, and vision insurance coverage
- Flexible work environment with remote-first culture
- Paid time off and holiday closures with generous vacation policies
- Professional development support and continuous learning programs
- Wellness and mental health support programs
- Inclusive, collaborative engineering culture focused on innovation and growth
Requirements:
Benefits:
Benefits
Equity Compensation
Equity opportunities as part of a long-term incentive package
Health Insurance
Comprehensive health, dental, and vision insurance coverage
Learning Budget
Professional development support and continuous learning programs
inclusive engineering culture
Inclusive, collaborative engineering culture focused on innovation and growth
Paid Time Off
Paid time off and holiday closures with generous vacation policies
Remote-Friendly
Flexible work environment with remote-first culture
Wellness Stipend
Wellness and mental health support programs
Jobgether runs the largest remote job platform, effectively linking job seekers with over 200,000 flexible and remote opportunities that match their unique skills and preferences. Our focus is on enhancing the hiring process, ensuring efficiency while prioritizing the candidate experience, particularly in the growing health and wellness sector.
- Founded
- Founded 2020
- Employees
- 11-50 employees
- Industry
- Professional Services