Careers - Senior ML/AI Modeler, Risk Automation Machine Learning

Block

Remote

Quick summary

Work type
Remote
Location
Canada
Salary
$228,700–$343,100 / yr
Posted
6 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $211k
This role $286k
$148k most similar roles pay here $364k

This role pays more than 93% of similar roles. Most pay $174,990–$246,150 — the shaded band above. At the midpoint, this role pays about $286k versus about $211k for comparable roles.

Based on 240 similar postings.

Employer

About Block

Block, Inc. (formerly Square) is a financial technology company operating the Square merchant payments ecosystem, Cash App peer-to-peer payments, TIDAL music streaming, and Bitcoin-focused financial services. Industry: Financial Technology & Payments

Block currently has 138 open roles on FindRole.

Listed pay typically runs $180,000–$270,000 across 61 roles with salary data.

Most-posted roles

View all roles at Block

At a glance

TL;DR · Careers - Senior ML/AI Modeler, Risk Automation Machine Learning

Apply Now Log in to save

As a Senior Machine Learning Engineer on Block’s Risk Automation ML team, you will work globally with Product, Engineering, and Operations to automate risk and compliance investigations using agentic and generative AI. Your daily tasks include deploying AI copilot and autopilot systems at scale to enhance analyst productivity and streamline decision-making processes. You’ll own the entire system lifecycle from API integration and advanced prompt tuning to productionization and monitoring, leveraging diverse datasets like payment transactions and user profiles. Key responsibilities involve collaborating with cross-functional teams to deploy robust ML/AI solutions in real-time environments using Python, PyTorch, Snowflake, and cloud services (GCP & AWS). Ideal candidates have 8+ years of full-stack ML experience, a master’s degree in a technical field, and expertise in AI engineering and large language models. This role demands leadership skills to drive strategic roadmaps and deliver high-impact business solutions.

Skills

Python Pytorch Snowflake Airflow AWS GCP LLMs Claude Code Codex Openclaw CI/CD MLOps NLP Transformer Models

What you'll do

  • Experiment and deploy AI copilot and autopilot systems to enhance analyst productivity.
  • Own the entire system lifecycle from API integration to production monitoring.
  • Build transformer-based ML models using diverse data sets for improved detection tasks.
  • Collaborate with cross-functional teams to deploy and maintain high-performance production systems.
  • Utilize Python ML stack, LLMs, Pytorch, Snowflake, Airflow, and cloud services in daily work.

What we're looking for

  • 8+ years of machine learning modeling experience with full stack ML expertise.
  • Masters or advanced degree in computer science, data science, operations research, applied math, stats, physics, or related field.
  • 3+ years of AI engineering and large language model experience.
  • End-to-end experience building and deploying ML/AI systems to production at scale.
  • Ability to independently own and drive cross-functional programs with significant business impact.
  • Proficiency in Python ML stack, LLMs, PyTorch, Snowflake, Airflow, and cloud services (GCP & AWS).
  • Curious mindset for identifying creative solutions that demonstrate value through first principles thinking.

Related searches

More Careers jobs Remote Careers jobs All jobs at Block

More like this

Similar roles

Careers - Senior Data Scientist, AI & Model Risk

Block

New York, NY 10 days ago $163,600–$225,000
Python LLMs Transformer models RAG systems AI testing methodologies Data privacy principles Encryption Access controls SHAP LIME NIST AI RMF ISO 42001 FFIEC IT Examination Handbook Model Risk Management CI/CD Regulatory compliance AI governance frameworks Explainability tools
Save

Careers - Senior Data Scientist, AI & Model Risk

Block

San Francisco, CA 10 days ago $163,600–$225,000
Python LLMs Transformer models RAG systems AI testing methodologies Data privacy principles Encryption Access controls SHAP LIME NIST AI RMF ISO 42001 FFIEC IT Examination Handbook Model Risk Management CI/CD Regulatory compliance AI governance frameworks Explainability tools
Save