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Managing Machine Learning Engineer - Job Opportunity at Allstate

Remote, US
Full-time
Senior
Posted: May 2, 2025
Remote
USD 160,000 - 235,000 per year

Benefits

Flexible work environment
Professional development opportunities
Comprehensive benefits package
Remote work options
Collaborative team culture

Key Responsibilities

Lead and mentor a team of junior and senior Machine Learning Engineers
Drive implementation of machine learning solutions across full lifecycle
Design and develop RAG applications and LLM-based solutions
Manage complex ML projects from conception to deployment
Collaborate with cross-functional teams to deliver business value
Balance traditional modeling approaches with emerging GenAI solutions

Requirements

Education

Bachelor's or Master's degree in Computer Science, Electrical Engineering, Physics, Mathematics, Statistics, or another quantitative major

Experience

5+ years

Required Skills

Python Java C++ PyTorch TensorFlow Scikit-learn Natural Language Processing Computer Vision Knowledge Representation Deep Learning Cloud Services (AWS, Azure, GCP) Machine Learning Algorithms
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Sauge AI Market Intelligence

Industry Trends

The integration of GenAI with traditional ML approaches represents a significant shift in enterprise AI strategy, indicating a mature ML practice Insurance industry is rapidly moving towards AI-driven decision making and customer service automation, particularly in claims processing and risk assessment Growing demand for ML leaders who can balance technical expertise with team management capabilities Increased focus on RAG applications suggests a strategic move towards leveraging company-specific knowledge bases with LLM capabilities

Salary Evaluation

The offered salary range of $160,000-235,000 is competitive for a senior ML leadership role, particularly considering the remote nature of the position. This aligns with current market rates for experienced ML leaders in the insurance/financial services sector

Role Significance

Based on the description and organization structure, likely leading a team of 4-7 ML engineers with varying experience levels
This is a senior technical leadership position with significant influence on Allstate's ML strategy and implementation. The role combines hands-on technical work with team leadership, indicating a player-coach model that maintains technical depth while developing leadership capabilities

Key Projects

Implementation of large language model applications for customer service automation Development of RAG systems for internal knowledge management Risk assessment and pricing optimization models Customer experience personalization initiatives Claims processing automation systems

Success Factors

Strong balance of technical expertise and leadership skills Ability to evaluate and implement both traditional ML and emerging AI solutions Experience in full lifecycle ML deployment including infrastructure considerations Strong communication skills for cross-functional collaboration Track record of delivering measurable business value through ML solutions

Market Demand

Very high demand, particularly due to the combination of technical ML expertise and team leadership requirements. The insurance industry's accelerating digital transformation creates strong demand for ML leaders who understand both traditional modeling and emerging AI technologies

Important Skills

Critical Skills

Deep understanding of ML algorithms and principles - essential for technical leadership and strategic decision-making Experience with LLMs and RAG applications - critical for current strategic initiatives Team leadership and mentoring capabilities - crucial for role success and team development Cloud services expertise - fundamental for modern ML infrastructure

Beneficial Skills

Experience in insurance industry ML applications Knowledge of MLOps and deployment automation Familiarity with regulatory compliance in ML applications Experience with distributed teams and remote collaboration

Unique Aspects

Emphasis on both traditional ML and GenAI indicates a mature and forward-thinking ML practice
Player-coach leadership model allows for continued technical growth while developing leadership skills
Focus on RAG applications suggests sophisticated approach to leveraging proprietary data
Strong emphasis on practical implementation and business value rather than pure research

Career Growth

Typical progression to director-level role in 2-4 years, depending on business impact and leadership capabilities

Potential Next Roles

Director of Machine Learning Chief AI Officer VP of AI/ML Strategy Head of AI Innovation

Company Overview

Allstate

Allstate is a leading insurance provider with a 90+ year history of innovation in risk management and customer protection. The company is actively investing in AI/ML capabilities to transform its digital operations

Fortune 100 company with strong market presence in insurance and financial services, actively competing in the digital transformation space
Major national presence with significant investment in remote work capabilities and distributed teams
Progressive technology culture with emphasis on innovation, collaboration, and work-life balance
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