Senior Staff Applied ML Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Investigate and analyze data utilizing Python, pandas, and PySpark (or comparable tools).

• Employ techniques such as matrix factorization, clustering, and dimensionality reduction to comprehend and prepare data for modeling, as well as to uncover and label latent factors (e.g., user behavior patterns, content/topic clusters, expertise dimensions).

• Develop, fine-tune, and deploy machine learning models for:

• Categorization / classification

• Recommendations and similarity

• Various prediction or ranking tasks that enhance product features.

• Design and implement AI-driven data ingestion processes that convert unstructured inputs (tickets, emails, forms, messages, logs, etc.) into structured data that can be utilized by models and downstream systems.

• Create workflows where AI can:

• Auto-fill or suggest essential fields and metadata.

• Proactively request missing or unclear information from users/customers (e.g., through email or messaging).

• Present similar past items or solutions to aid humans in decision-making.

• Completely manage simple, repetitive “Level 1” style requests end-to-end when appropriate.

• Collaborate closely with engineers to integrate models and workflows into production systems with adequate monitoring, fallback mechanisms, and safety measures.

• Partner with various product teams to assist them in identifying and defining AI opportunities within their domains.

• Establish patterns, templates, and best practices for data ingestion, feature creation, model usage, and evaluation that teams can leverage.

• Act as a trusted advisor and technical leader:

• Offer design and architecture advice on data and ML-intensive features.

• Participate in projects to tackle the most complex modeling or workflow automation challenges when teams encounter difficulties.

• Mentor and support junior data/ML engineers and analysts:

• Conduct reviews of code and models.

• Collaborate with them on challenging problems.

• Assist them in developing sound intuitions regarding metrics, evaluation, and operational reliability.

• Aid in establishing and promoting standards for experimentation, documentation, and responsible AI usage across teams.

⛳️ Requirements

• Over 5 years of experience in data science, ML engineering, or a similar applied role, with a proven track record of delivering production data/ML features.

• Strong proficiency in Python and experience with pandas for data analysis.

• Familiarity with PySpark or other frameworks for distributed data processing.

• Thorough understanding of ML fundamentals, including:

• Supervised learning and classification models

• Matrix factorization / embeddings / latent factor models

• Feature engineering and model evaluation (offline metrics and online experiments)

• Proficiency in PyTorch (or a similar deep learning framework) and associated ML tools.

• Strong SQL skills and experience with modern data warehouses/data lakes.

• Comfort with APIs, microservices, and the production integration of ML models, considering performance and reliability factors.

• Experience functioning as a technical lead or senior individual contributor across multiple teams or projects.

• Demonstrated ability to translate business challenges into data/ML initiatives and clearly communicate trade-offs to non-ML stakeholders.

• Proven track record of mentoring junior engineers/analysts and enhancing team practices (e.g., review culture, testing, monitoring).

• Excellent communication skills with the capability to foster alignment among product, engineering, and operations teams.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Generous paid time off and flexible work arrangements.

• Opportunities for professional development and continuous learning.

• Collaborative and inclusive work environment.