Sr ML Engineer

Akaasa Technologies; Town of Florida (NY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Akaasa Technologies in Davie, FL is hiring a Sr ML Engineer to lead the design, development and deployment of scalable machine learning systems powering Customer 360, personalization and recommendation engines. You will collaborate with Data Engineering and MLOps to ship production-ready models and AI capabilities across domains.

The role requires strong hands-on leadership with experience building production-grade ML systems, real-time inference, and familiarity with Databricks, Snowflake and

Qualifications

• 8+ years of Machine Learning Engineering or Applied AI experience.
• 3+ years in a Lead, Principal, or Senior Technical Leadership role.
• Proven experience delivering production-grade machine learning systems.

Responsibilities

• Lead ML strategy and development across multiple business domains.
• Build and operationalize ML solutions including recommendation engines and personalization.
• Collaborate with Data Engineering and MLOps to deploy real-time inference systems.
• Provide technical leadership across DS, Engineering and MLOps teams.

Skills

Databricks

MLflow

Python

TensorFlow

PyTorch

Scikit-learn

Real-time inference

Recommendation engines

Personalization

Customer 360

MLOps

GenAI

Identity Graph

Snowflake

LLM-powered apps

Tools

Snowflake

Job description

Sr ML Engineer

Location: Davie, FL - Hybrid

Position Overview

We are seeking an experienced Lead Machine Learning Engineer to lead the development and operationalization of machine learning solutions that power Customer 360, recommendation engines, customer intelligence, personalization, and next-generation AI experiences.

This role will be responsible for designing scalable ML systems, partnering closely with Data Engineering and MLOps teams, and driving production-ready machine learning capabilities across multiple business domains.

The ideal candidate has successfully built recommendation engines, customer prediction models, and AI-driven solutions in highly scalable customer-centric environments.

Key Responsibilities

• Machine Learning Strategy & Development
• Lead development of machine learning solutions supporting:
• Recommendation engines
• Customer segmentation
• Churn prediction
• Customer value prediction
• Offer optimization
• Content personalization
• Design, train, evaluate, and deploy predictive models.
• Create reusable ML frameworks and model development standards.
• Customer Intelligence & Personalization
• Leverage Customer 360 and Identity Graph capabilities to improve prediction accuracy.
• Develop intelligent customer insights and personalization capabilities.
• Build models that improve customer engagement, retention, and loyalty outcomes.
• Collaborate with business leaders to align machine learning priorities with strategic objectives.
• AI & Next-Generation Capabilities
• Support development of domain-specific AI agents.
• Partner with engineering teams on AI-powered business experiences.
• Contribute to LLM-enabled solutions and intelligent assistant initiatives.
• Evaluate emerging AI capabilities and opportunities for enterprise adoption.
• Production ML & Scaling
• Work closely with MLOps Engineers to operationalize models.
• Develop scalable real-time inference solutions.
• Build monitoring, model validation, and retraining processes.
• Optimize model performance and reliability in production.
• Technical Leadership
• Provide technical leadership across Data Science, Engineering, and MLOps teams.
• Mentor ML Engineers and Data Scientists.
• Lead architecture discussions and model review sessions.
• Establish best practices for enterprise AI delivery.

Required Qualifications

• 8+ years of Machine Learning Engineering or Applied AI experience.
• 3+ years in a Lead, Principal, or Senior Technical Leadership role.
• Proven experience delivering production-grade machine learning systems.
• Strong expertise with:
• Databricks
• MLflow
• Python
• Machine Learning Frameworks (TensorFlow, PyTorch, Scikit-learn)
• Real-time inference architectures
• Experience building:
• Recommendation systems
• Personalization engines
• Predictive analytics solutions
• Customer intelligence platforms
• Deep understanding of feature engineering and ML lifecycle management.
• Experience partnering with Data Engineering teams to design ML-ready datasets.
• Preferred Qualifications
• Customer 360 implementation experience.
• Identity Graph experience.
• Hospitality, Gaming, Entertainment, Retail, Loyalty, or Consumer Digital experience.

Experience with:

• Snowflake
• MLOps practices
• GenAI solutions
• Agentic AI architectures
• LLM-powered applications
• Real-time recommendation platforms
• Experience supporting enterprise AI transformation initiatives.
• Success Profile
• The ideal candidate is a hands-on ML leader who:
• Has successfully built and deployed machine learning products at scale.
• Thrives in fast-moving, greenfield environments.
• Can translate business challenges into AI solutions.
• Balances architecture, experimentation, and delivery.
• Has a builder mentality and can accelerate value creation immediately.
• Top Screening Keywords for Both Roles
• Customer 360
• Identity Graph
• Recommendation Engine
• Databricks
• Snowflake
• Machine Learning
• AI/ML Delivery
• Streaming Data
• Personalization
• Customer Intelligence
• MLOps
• Real-Time Inference
• Hospitality/Gaming
• Greenfield Build
• Data Products
• Domain-Oriented Architecture