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AuditBoard

Senior Software Engineer II- Machine Learning

Posted 8 Days Ago
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Remote
Hiring Remotely in Canada
Senior level
Remote
Hiring Remotely in Canada
Senior level
As a Senior Software Engineer II in Machine Learning, you'll design and implement AI systems, focusing on production-grade ML techniques, collaborating with cross-functional teams, and ensuring systems are reliable and maintainable.
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Who We Are

Having surpassed $300M ARR and continuing to grow, AuditBoard is the leading audit, risk, ESG, and InfoSec platform on the market. More than 50% of the Fortune 500, including 7 of the Fortune 10, leverage our award-winning technology to move their businesses forward with greater clarity and agility. And our customers love us: AuditBoard is top-rated on G2.com and Gartner Peer Insights.
At AuditBoard, we inspire each other to innovate and are proud of what we are producing. We spend each day thinking of new ways to help our customers and contribute to the greater good of our company and our surrounding communities. We are all about assisting each other and breaking through barriers to create the most loved audit, risk, ESG, and InfoSec platform by our customers. This is how we have become one of the 500 fastest-growing tech companies in North America for the sixth year in a row, as ranked by Deloitte!

Why This Role is Exciting

We are looking for a Senior Software Engineer with strong machine learning experience to help build and scale intelligent, production-grade systems that power our risk and compliance platform. In this role, you’ll work at the intersection of software engineering and applied machine learning, shipping real customer-facing features that leverage both classical ML techniques and modern approaches like Large Language Models (LLMs).

You’ll be embedded in a product engineering team, owning systems end-to-end—from API design and data pipelines to model integration, evaluation, and long-term maintainability. If you enjoy building robust software systems and applying ML pragmatically (not experimentally) to solve real customer problems, this role is for you.

Responsibilities
  • Design and implement AI-powered systems using a mix of classical ML techniques and modern LLM-based approaches, frequently leveraging managed Azure AI/ML services as building blocks.

  • Apply a range of techniques—from classical ML to LLM-based approaches (RAG, prompt engineering, fine-tuning, semantic search)—with a strong focus on reliability, performance, and maintainability

  • Collaborate closely with product managers and designers to deliver high-quality, customer-focused features.

  • Write clean, testable, well-documented code and contribute to shared engineering standards.

  • Author clear design docs that explain system behavior, tradeoffs, and long-term implications.

  • Debug and resolve production issues across application code, data, and ML components.

  • Evaluate ML systems using metrics and real-world signals, and iteratively improve them.

  • Participate fully in an Agile development lifecycle, contributing to planning, reviews, and retrospectives.

  • Stay current on ML and software engineering best practices, adopting new tools thoughtfully and pragmatically.

Attributes of a Successful Candidate:
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field—or equivalent practical experience.

  • 4+ years of professional software engineering experience, with meaningful exposure to machine learning in production systems.

  • Strong ability to design and build scalable, production-quality software.

  • Excellent programming skills in Python

  • Hands-on experience applying machine learning models in real systems, including model integration, inference, and evaluation.

  • Familiarity with ML frameworks such as PyTorch, TensorFlow, Hugging Face, or scikit-learn.

  • Experience or interest in search, information retrieval, ranking, or recommendation systems.

  • Product mindset: you care about user impact, not just technical elegance.

  • Strong communication skills and comfort working cross-functionally.

Preferred
  • Experience with Node.JS and TypeScript

  • Experience working on SaaS web applications

  • Basic understanding of distributed systems

  • Bonus: Docker, Kubernetes experience, AWS/Azure cloud infrastructure

Our Company Values

  • Customer obsession: Apply relentless focus on listening to and understanding customers as the core of everything we do

  • Win, together: Drive to be the best while supporting each other’s success

  • Gritty resilience: Thrive in a fast-paced and dynamic environment, balancing immediate priorities with big-picture strategic goals

  • Personal improvement: Stay eager to share insights, seek feedback, and continuously learn

  • Constant innovation: Challenge the status quo and drive improvements

Perks*

  • Launch a career at one of the fastest-growing SaaS companies in North America!

  • Live your best life (LYBL)! $200/mo for anything that enhances your life

  • Comprehensive employee health coverage (all locations)

  • 401K with match (US) or pension with match (UK)

  • Competitive compensation & bonus program

  • Flexible Vacation (US exempt & CA) or 25 days (UK)

  • Time off for your birthday & volunteering

  • Employee resource groups

  • Opportunities for team and company-wide get-togethers!

*perks may vary based on eligibility/location

Please note that background checks are required. Qualified Applicants with arrest or conviction records will be considered for Employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. This role may have access to highly sensitive data, including employee data, customer data, company financials, and proprietary product information.
We love building strong partnerships, but please note that AuditBoard cannot accept unsolicited resumes from agencies. Any submissions without a signed agreement in place will not create a fee obligation.

 

#LI-Remote

Top Skills

AWS
Azure
Azure Ai/Ml
Docker
Hugging Face
Kubernetes
Node.js
Python
PyTorch
Scikit-Learn
TensorFlow
Typescript

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