Staff Machine Learning Engineer

2 weeks ago

Toronto, Ontario, Canada KenkoTech Futures Full time $180,000 - $250,000 per year

Job Title:
Sr. Machine Learning Engineer

Location:
USA / Canada (On-Site / Remote)

Stage:
Series B (~$250M funding)

PLEASE FOLLOW THE KENKOTECH PAGE AND CONNECT WITH THE JOB POSTER

About the Opportunity

We're partnering with a cutting-edge biotech using artificial intelligence to reinvent how medicines are discovered. Their AI platform unites machine learning, bioinformatics, and massive genomic datasets to uncover drug targets and mechanisms unreachable through traditional approaches.

As a
Senior ML Engineer
, you'll be the driving force behind the systems powering this innovation. You'll design, build, and scale high-performance ML infrastructure - training pipelines, inference frameworks, and reproducible workflows that bring AI models to life. Working closely with world-class ML scientists, engineers, and biologists, you'll turn data into discovery and technology into new medicines.

Key Responsibilities

  • Design, develop, and maintain reliable ML workflows for model training, evaluation, and large-scale inference
  • Build scalable, reproducible data pipelines that power end-to-end machine learning experiments
  • Integrate model development processes with experiment tracking and reproducibility tools (e.g., Weights & Biases)
  • Collaborate with scientists and engineers to prototype, iterate, and deploy ML solutions into production environments
  • Promote best practices in software engineering, including modular design, code review, testing, and CI/CD automation
  • Mentor team members and contribute to the continuous improvement of the ML engineering function

Qualifications

  • 3+ years of experience as an ML Engineer, Software Engineer, or related role focused on machine learning systems
  • Strong proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or JAX
  • Solid understanding of software architecture, design patterns, and engineering best practices
  • Hands-on experience with containerization and orchestration tools (Docker, Kubernetes)
  • Strong collaborator who thrives in cross-functional environments involving engineering, ML, and biology teams
  • Ability to mentor and elevate the technical capabilities of peers

Why Join

  • Be part of a mission-driven company at the forefront of AI and computational biology
  • Contribute to real-world applications where your systems directly impact the creation of new genetic medicines
  • Work in a collaborative, innovation-focused culture with world-class talent in ML, data science, and drug discovery
  • Competitive compensation and equity package, comprehensive benefits, flexible work environment, and strong emphasis on learning and growth

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