FlexHired LogoFlexHired
Logo of Braze

Braze

Senior Engineer, Machine Learning

Job Summary

This role involves designing and implementing scalable AI and machine learning platforms, with a focus on data-intensive products and production deployment of models. The candidate will collaborate closely with cross-functional teams to develop modular components using Python and cloud technologies like GCP, Kubernetes, and Airflow. Strong coding skills, experience with cloud platforms, and knowledge of supervised learning are essential. The position emphasizes best practices such as testing, modular design, and continuous integration, all within a supportive and growth-oriented environment.

Required Skills

Terraform
Data Architecture
SQL
Python
CI/CD
Machine Learning
Reinforcement Learning
Airflow
Data Science
Software Engineering
Object-Oriented Programming
Kubernetes
Code Reviews
Cloud Platforms
Unit Testing
GCP
FastAPI
BigQuery
Supervised Learning
Pair Programming
Integration Testing
Modular Design
AI Pipelines

Benefits

Competitive Compensation
Flexible Paid Time Off
Paid Parental Leave
Medical Insurance
Dental Insurance
Vision Insurance
Life Insurance
Disability Insurance
Equity
Professional Development
Employee Resource Groups
Fertility Benefits
Retirement Plans
Employee Stock Purchase Plans
Learning Stipend
Volunteer Opportunities
Community Building

Job Description

At Braze, we have found our people. We’re a genuinely approachable, exceptionally kind, and intensely passionate crew.

We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity – inside and outside our organization.

To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success.

Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture.

If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can’t wait to meet you.

WHAT YOU'LL DO

Do you enjoy working on data-intensive products? Come join our growing Engineering team to help design, improve and scale Braze's self-learning (reinforcement learning) AI platform. No toy datasets in notebooks - we’re implementing AI pipelines in production at scale! Learn tons about data architecture, data science, and self-learning AI. Work in a team that not only talks the talk of development best practices, but walks the walk - unit & integration tests, modular design, CI/CD, pair programming, code reviews - the works.

Responsibilities:

  • Use robust software engineering best practices to design, implement, and improve modular components in a cutting-edge ML product
  • Work closely with Braze customers to understand, translate and generalize particular use cases to generic platform components
  • Apply your extensive knowledge of Python and its ecosystem to produce clean, readable, and extendible code, and coach others on the team in doing the same
  • Collaborate with teams responsible for Braze’s product strategy and roadmap
  • Support teams implementing Braze for customers to ensure their success
  • Data Science/Back End: Python (Pyspark, Polars, Ibis), SQL, BigQuery, FastAPI
  • Architecture/DevOps: Kubernetes, Airflow, Terraform, GCP
  • We write well-tested, type-hinted, documented, modular code and use pre-commit hooks, CI/CD, and issue tracking for development

WHO YOU ARE

  • Exceptional coder: you write clean, object-oriented code; you care about good design and terse, testable APIs
  • Tinkerer: you regularly explore and learn new technologies and methods, especially in the data architecture and data science domains
  • Entrepreneurial: you proactively identify opportunities and risks, work around obstacles, and always seek creative ways to improve processes and outcomes
  • Structured and organized: you can structure a plan, align stakeholders, and see it through to execution
  • Clear communicator: you are able to express yourself clearly and persuasively, both in writing and speech
  • 2+ years of experience working with Python in a product setting, including 1+ years in a the data/machine learning ecosystem
  • Experience working with at least one major cloud platform (GCP, AWS, Azure, etc.)
  • Experience putting ML models into production
  • General understanding of supervised learning principles is a plus

#LI-Remote

WHAT WE OFFER

Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country here. More details on benefits plans will be provided if you receive an offer of employment.

From offering comprehensive benefits to fostering hybrid ways of working, we’ve got you covered so you can prioritize work-life harmony. Braze offers benefits such as:

  • Competitive compensation that may include equity
  • Retirement and Employee Stock Purchase Plans
  • Flexible paid time off
  • Comprehensive benefit plans covering medical, dental, vision, life, and disability
  • Family services that include fertility benefits and equal paid parental leave
  • Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
  • A curated in-office employee experience, designed to foster community, team connections, and innovation
  • Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
  • Employee Resource Groups that provide supportive communities within Braze
  • Collaborative, transparent, and fun culture recognized as a Great Place to Work®

ABOUT BRAZE
Braze is the leading customer engagement platform that empowers brands to Be Absolutely Engaging.™ Braze allows any marketer to collect and take action on any amount of data from any source, so they can creatively engage with customers in real time, across channels from one platform. From cross-channel messaging and journey orchestration to Al-powered experimentation and optimization, Braze enables companies to build and maintain absolutely engaging relationships with their customers that foster growth and loyalty.

Braze is proudly certified as a Great Place to Work® in the U.S., the UK, Australia, and Singapore. In 2025, we were recognized as one of Built In’s Best Places to Work. In 2024, we were included in U.S. News & World Report’s Best Companies to Work For (Top 10%) and recognized in Great Place to Work’s Fortune Best Medium Workplaces, Fortune Best Workplaces in Technology, Fortune Best Workplaces for Parents, and Fortune Best Workplaces for Women.
Additionally, we were featured in Great Place to Work UK’s Best Workplaces, Best Workplaces in Europe, Best Workplaces for Development, Best Workplaces for Wellbeing, Best Workplaces for Women, and Best Workplaces in Technology.

You’ll find many of us at headquarters in New York City or around the world in Austin, Berlin, Bucharest, Chicago, Dubai, Jakarta, London, Paris, San Francisco, Singapore, São Paulo, Seoul, Sydney and Tokyo – not to mention our employees in nearly 50 remote locations.

BRAZE IS AN EQUAL OPPORTUNITY EMPLOYER

At Braze, we strive to create equitable growth and opportunities inside and outside the organization.

Building meaningful connections is at the heart of everything we do, and that includes our recruiting practices. We're committed to offering all candidates a fair, accessible, and inclusive experience – regardless of age, color, disability, gender identity, marital status, maternity, national origin, pregnancy, race, religion, sex, sexual orientation, or status as a protected veteran. When applying and interviewing with Braze, we want you to feel comfortable showcasing what makes you you.

We know that sometimes different circumstances can lead talented people to hesitate to apply for a role unless they meet 100% of the criteria. If this sounds familiar, we encourage you to apply, as we’d love to meet you.

Please see our Candidate Privacy Policy for more information on how Braze processes your personal information during the recruitment process and, if applicable based on your location, how you can exercise any privacy rights.

Interested in this job?

Application deadline: Open until filled

Logo of Braze

Braze

Power customer-centric interactions between consumers and brands in real-time.

See more jobs
Date PostedJuly 16th, 2025
Job TypeFull Time
LocationRemote - Ontario
SalaryCompetitive rates
Exciting remote opportunity (requires residency in Canada) for a Senior Engineer, Machine Learning at Braze. Offering competitive salary (full time). Explore more remote jobs on FlexHired!

Safe Remote Job Search Tips

Verify Employer Thoroughly

Research the company's identity thoroughly before applying. Check for a professional website with contacts, active social media, and LinkedIn profiles. Verify details across platforms and look for reviews on Glassdoor or Trustpilot to confirm legitimacy.

Never Pay to Get a Job

Legitimate employers never require payment for applications, training, background checks, or equipment. Always reject upfront payment requests or demands for bank details, even if they claim it's for purchasing necessary work gear on your behalf.

Safeguard Your Personal Information

Protect sensitive data like SSN, bank details, or ID copies. Share this only after accepting a formal, written job offer. Ensure it's submitted via a secure company system or portal, never through insecure channels like standard email attachments.

Scrutinize Communication & Interviews

Watch for communication red flags: poor grammar, generic emails (@gmail), vague details, or undue pressure. Be highly suspicious of interviews held only via text or chat apps; legitimate companies typically use video or phone calls.

Beware of Unrealistic Offers

If an offer's salary or benefits seem unrealistically high for the work involved, be cautious. Research standard pay for similar roles. Offers that appear 'too good to be true' are often scams designed to lure you into providing information or payment.

Insist on a Formal Contract

Always secure and review a formal, written job offer or employment contract before starting work or sharing final personal details. Ensure it clearly defines your role, compensation, key terms, and conditions to avoid misunderstandings or scams.

Related Jobs

Full Time
Remote - Ontario, Canada
Full Time
Remote - Ontario, Canada
Full Time
Remote - Ontario, Canada
Full Time
Remote - Ontario, Canada
Full Time
Remote - Ontario, Canada

Subscribe Newsletter

Never miss a remote job opportunity. Subscribe to our newsletter today and receive exclusive job alerts, career advice, and industry insights delivered straight to your inbox.