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Senior Machine Learning Engineer
Location
Worldwide
Posted
115 days ago
Salary
0
Seniority
Senior
No structured requirement data.
Job Description
Senior Machine Learning Engineer
FreshBooks
Role Description 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 Qualifications - 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)
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