ML Ops Engineer
Toronto, Ontario /
Engineering – Machine Learning /
BenchSci's vision is to bring medicine to patients 50% faster by 2025. We're doing this by empowering scientists with the world’s most advanced biomedical artificial intelligence to run more successful experiments. Backed by F-Prime, Gradient Ventures (Google’s AI fund), and Inovia Capital, our platform accelerates science at 15 top 20 pharmaceutical companies and over 4,300 leading research centers worldwide. We're a CIX Top 10 Growth company, certified Great Place to Work®, and top-ranked company on Glassdoor.
We are seeking an ML Ops Engineer to join our growing R&D team! Reporting into the Engineering Manager, you will operationalize machine learning experiments into production-grade deployments. Successful candidates for this role will have a great appreciation for science, comfort with the nuances of continuous integration and continuous deployment in the machine learning lifecycle, and a results-oriented approach to the work they do. In this position, you will play a key role in helping BenchSci scale as we continue to make a long-term impact on the future of scientific discovery and progress.
- Drive core components of our ML technical roadmap concerning continuous deployment, model serving, and performance monitoring
- Create and implement reference architectures for both training and inference at scale, collaborating and knowledge-sharing with our Core Infrastructure team
- Stay informed about the state-of-the-art, using our available cloud and on-premise infrastructure to continuously level-up our ML ecosystem
- Help model owners produce clean, tractable, and highly performant machine learning through code review
- Advocate for code and process improvements across your team, and help to define best practices based on personal industry experience and research
- Participate in sprint planning, estimations, and reviews
- Work with teammates to ensure high-quality deliverables
- 3+ years of software engineering experience, preferably in Python
- Experience with reference architectures for Machine Learning in cloud, on-premise, and hybrid environments
- Strong Linux system administration skills and pride in the cleanliness and reproducibility of infrastructure
- Familiarity with industry standards such as MLFlow, Kubeflow, and DVC
- Experience with container orchestration systems such as Kubernetes (we use GKE)
- Exposure to automated testing and CI/CD in the ML context
- Understanding of fundamental ML concepts like metrics, biases, and datasets
- A constant desire to grow and learn
- Strong cross-team communication and collaboration skills
- A desire to see teammates succeed together
Nice to haves, but not mandatory qualifications:
- Research publications in ML/AI-related fields
- Experience productionalizing ML models
- Experience with TensorFlow, PyTorch, and image processing libraries such as OpenCV and scikit-image
- Background in Life Science
- Experience with Spark 2.x or later
- Experience with pipelining/orchestration frameworks such as Airflow or Beam
- Experience with hermetic build tools such as Bazel
Our benefits and perks:
- A compensation package that includes equity options in the company
- An annual Executive Health Assessment at Medcan: All employees get the “executive treatment”
- Effectiveness coaching for managers: Onsite, personalized coaching from a trained clinical psychologist
- Mental health tools and support: Optional mindfulness sessions and a free Headspace account
- Complimentary genome sequencing from 23andMe: Find out what your DNA says about your health, traits, and ancestry
- Three weeks of vacation, plus another week: Get 15 days to use anytime, and we’re closed Dec 25-Jan 1
- Additional days off: Company summer day, your birthday, and earn +1 vacation day annually
- Work from anywhere flexibility: Every day right now, and up to 4 days per week once we return to the office
- An onsite gym: Keep fit, conveniently, with a Peloton and other great equipment
- A great benefits package: Including health and dental
Here at BenchSci, these are our core values:
Focused: We focus on what will drive the greatest impact at all times.
Advancement: We believe in continuous growth, and discovering new ways to do things better. This applies to our product and business, but also to ourselves.
Speed: We recognize that without a sense of urgency, our team, our product and our mission lose their value.
Tenacity: What we’re trying to do isn’t easy, but we hire the best people, and give them the autonomy, tools, and resources to succeed. The hard work is up to them.
Transparency: We believe that sharing diverse ideas and information creates strong teams. Our success stems from research, collaboration, feedback, and trust.
BenchSci is an equal opportunity employer. We value diversity and are committed to fostering an inclusive environment. All four of our cofounders are immigrants to Canada, as are many of our employees. We welcome your fresh perspectives and ideas.