Senior Staff Applied ML Engineer

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

📋 Description

• Empower product teams by educating, coaching, and guiding them on best practices in data and machine learning.

• Lead by example through conducting intricate data analysis and machine learning modeling, architecture, and implementation tasks as necessary to enhance team performance while mentoring less experienced data and ML professionals.

• Investigate and assess data using Python, pandas, and PySpark.

• Apply matrix factorization, clustering, dimensionality reduction, and similar techniques to analyze and prepare data for modeling, as well as to identify and classify latent factors (such as user behavior patterns, topic/content clusters, and dimensions of expertise).

• Develop, optimize, and deploy machine learning models for categorization/classification, recommendations, similarity, and other predictive or ranking tasks that enhance product functionalities.

• Design and establish AI-driven ingestion processes that transform unstructured inputs (such as tickets, emails, forms, messages, logs, etc.) into well-organized data suitable for modeling and downstream systems.

• Create workflows that enable AI to automatically populate or suggest essential fields and metadata.

• Collaborate closely with engineers to integrate models and workflows into production systems, ensuring proper monitoring, fallback options, and safety measures.

⛳️ Requirements

• Over 5 years of experience in data science, machine learning engineering, or a comparable applied role.

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

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

• Comprehensive understanding of machine learning principles, including:

• Supervised learning and classification models.

• Matrix factorization, embeddings, and latent factor models.

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

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

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

• Comfort with APIs, microservices, and the production integration of machine learning models, taking into account performance and reliability aspects.

• Experience acting as a technical lead or senior individual contributor across various teams or projects.

• Proven capability to translate business challenges into data/ML initiatives and to articulate trade-offs to stakeholders without a machine learning background clearly.

• A history of mentoring junior engineers and analysts while enhancing team practices (including review culture, testing, and monitoring).

🏝️ Benefits

• Health insurance

• 401(k) matching

• Flexible working hours

• Paid time off

• Professional development opportunities