Software Developer

Daisy Intelligence

Daisy Intelligence

Software Engineering
Toronto, ON, Canada
Posted on Wednesday, May 19, 2021
Daisy Intelligence is a leader in developing intelligent automation, offering recognized technology that is already being leveraged by a growing roster of global clients and partners. We deliver impactful decisions that increase job satisfaction while growing retailers and insurers’ top and bottom line.
Join us in building a future where computing machines improve our lives: We are hiring a Sr. Machine Learning Developer to help us manage the production of Machine Learning application development at scale while nurturing our growth mindset.
How We Work:
With a culture of ownership that empowers each employee to make a difference, we offer more than a place to work.
Our high-performing engineering team is driven to create machine intelligence that is balanced with the human elements required to maximize efficiency. We operate within a SaaS infrastructure, practicing agile methodologies with 2-week sprints and continuous integration. We aim to deploy our products on a weekly to bi-weekly cadence.
Who you are:
At Daisy we’re building a team of innovative, results driven, and curious people who are passionate about team and client success. We offer a truly unique autonomous (no code, no infrastructure, no bias) AI system that elevates our customers - enabling them to focus on delivering their mission and servicing their own customers. With our cutting-edge technology, we offer our employees an opportunity to continuously innovate and make an impact.
We are a fast-paced and client-based organization, focusing on sales and client retention. We guarantee change and shifting priorities as we endeavour to meet client needs. We are looking for driven, results-oriented, creative problem solvers who define themselves as both a subject matter expert and an individual that isn’t afraid to wear multiple hats. You have a heightened sense of urgency and curiosity and are comfortable with a changing work environment. You also understand the value of client centricity.

What You Bring:

  • Bachelor's or Master’s degree in a quantitative discipline (Engineering, Computer Science or Mathematics).
  • Experience leading and/or implementing production Machine Learning solutions in a GCP or similar cloud environment, leveraging MLOps best practices and tools.
  • Strong experience and skills in Operations research specifically in Optimization, Reinforcement learning or Control Theory approaches
  • Strong experience and skills in SQL and Hadoop.
  • Strong programming experience in C/C++
  • Exposure to mathematical modelling with tools like SAS or R
  • Experience building and operating data pipelines and warehouses at scale (distributed low-latency processing)
  • Machine learning expertise to help the technical team in developing and enhancing Daisy’s existing products.
  • Experience clearly communicating domain-specific techniques and processes to technical and non-technical audiences.
  • A strong work ethic, you work best in a high-performing environment and can balance competing priorities with continuous deadlines for delivery.
  • You are accountable and live up to your commitments and are not afraid to work exceeding hard to succeed.
  • You are a hands-on leader who will demonstrate and mentor your team by participating and developing software as a member of the development team
  • You are curious and strive to understand the customer perspective to bring creative solutions to complex problems involving multiple stakeholders.
  • You are quality focused and ensure that Daisy client facing deliverables are of the highest quality in the eyes of our customers.

Bonus Points For:

  • As Daisy is a global organization, the ability to travel to client locations is preferred.
  • A deep understanding of how cross-functional product teams work at a software product company and experience managing such teams
  • Experience with high-performance computing
  • Experience in HIVE
  • Experience leading and/or implementing distributed low-latency processing solutions
  • Knowledge of DevOps and Continuous Integration
  • Experience using Big Query, Docker, and Kubernetes

What We’re Offering:

  • Impactful Work: Deliver clients 3 – 5 % top-line revenue growth with intelligent automation.
  • Innovation: Leverage cutting-edge technology that delivers incremental value and verifiable financial results to Fortune 500 Companies.
  • Giving Back: We take every opportunity to give back to our community through volunteering and fundraising; our corporate philanthropy includes but is not limited to our sponsorship of Motionball.
  • A High-Performance Team: Become part of a team of creative, results-driven, and curious people who truly care about team and client success
  • Other Perks and Rewards: Stock options, an annual performance bonus (dependant on year end corporate financial results), group health benefits, 3 weeks vacations, open ended sick leave, and a hybrid office environment.
Daisy is for Everybody
If this sounds like a fit and you’d like to learn more, don’t hesitate to reach out. We still encourage those that don’t meet every single requirement to apply – there’s a possibility you’re the right candidate for this role, or others in our pipeline.
We are committed to making diversity and inclusion an integral part of the way we work – both internally and externally. We view diversity and inclusion as a strength and advantage in building a culture that fosters belonging and in building an innovative, high-performance team that brings their authentic selves to work.
Please advise us if you require any accommodations through the interview process. Our interviews are currently conducted remotely via phone or video call.
Hybrid working environment
We fundamentally believe a hybrid working environment provides an optimal balance of productive work, enhanced collaboration and fostering company culture.
Although we are currently working remotely, we plan to return to a hybrid working model in the Summer of 2023 where we will work 3 days in the office and 2 days remotely.