Senior Machine Learning Engineer
As a Senior Machine Learning Engineer at FreshBooks, you will own the full machine learning lifecycle, from early experimentation and prototyping to deployment and monitoring in production. You will work on moderately complex problems, refine ML processes, and support teammates through mentorship and collaboration. You will help deliver ML-powered features while optimizing systems for reliability, performance, and rapid experimentation. This role is primarily focused on machine learning, with supporting software engineering skills to enable production deployment. This role is ideal for someone who enjoys taking ideas from concept to customer impact.
NOTE: This role can be worked remotely from the above location.
What You’ll Do
Design, prototype, and validate machine learning models for product features and internal tools
Own the ML lifecycle from experimentation through production deployment and monitoring
Partner with Data Engineering and Product Engineering to integrate models into batch and online systems
Build and maintain shared feature pipelines, including documentation and versioning
Write production-ready code with testing, observability, and monitoring
Design experiments (A/B test, pre/post analysis) and interpret results to guide product and business decisions
Improve ML reliability through retraining workflows, drift detection, and root cause analysis
Design and build end-to-end pipelines for classification, ranking, embeddings, or generation tasks
What You’ll Bring
5+ years of experience in data science, applied ML, or ML engineering roles
Strong foundation in supervised and unsupervised learning, statistical modeling, and experimentation techniques
Experience developing and shipping ML models in production (batch or real-time)
Strong Python and SQL skills with experience working with structured and unstructured data
Hands-on experience building and deploying ML or LLM-based systems (e.g. retrieval-augmented generation, embeddings, prompt tuning)
Familiarity with cloud infrastructure and ML tools, ideally on Google Cloud Platform (e.g. Vertex AI, BigQuery, Cloud Composer, Kubernetes).
Experience working with CI/CD pipelines, containerization (Docker), and job orchestration tools (Airflow, dbt, etc.).
Strong communication skills and ability to explain technical concepts to non-technical stakeholders
You’ll Stand Out If You Have
Experience working with agentic models
Familiarity with LLM orchestration frameworks (e.g., ADK, LangChain, Semantic Kernel, Haystack)
A background in software engineering (e.g., system design, APIs, or distributed systems)
#LI-SR1 #LI-Remote
Apply To This Job
NOTE: This role can be worked remotely from the above location.
What You’ll Do
Design, prototype, and validate machine learning models for product features and internal tools
Own the ML lifecycle from experimentation through production deployment and monitoring
Partner with Data Engineering and Product Engineering to integrate models into batch and online systems
Build and maintain shared feature pipelines, including documentation and versioning
Write production-ready code with testing, observability, and monitoring
Design experiments (A/B test, pre/post analysis) and interpret results to guide product and business decisions
Improve ML reliability through retraining workflows, drift detection, and root cause analysis
Design and build end-to-end pipelines for classification, ranking, embeddings, or generation tasks
What You’ll Bring
5+ years of experience in data science, applied ML, or ML engineering roles
Strong foundation in supervised and unsupervised learning, statistical modeling, and experimentation techniques
Experience developing and shipping ML models in production (batch or real-time)
Strong Python and SQL skills with experience working with structured and unstructured data
Hands-on experience building and deploying ML or LLM-based systems (e.g. retrieval-augmented generation, embeddings, prompt tuning)
Familiarity with cloud infrastructure and ML tools, ideally on Google Cloud Platform (e.g. Vertex AI, BigQuery, Cloud Composer, Kubernetes).
Experience working with CI/CD pipelines, containerization (Docker), and job orchestration tools (Airflow, dbt, etc.).
Strong communication skills and ability to explain technical concepts to non-technical stakeholders
You’ll Stand Out If You Have
Experience working with agentic models
Familiarity with LLM orchestration frameworks (e.g., ADK, LangChain, Semantic Kernel, Haystack)
A background in software engineering (e.g., system design, APIs, or distributed systems)
#LI-SR1 #LI-Remote
Apply To This Job