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# Senior Machine Learning Engineer - Data Science & Analytics

- **Company:** Akaasa Technologies
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $160,000.0 - $190,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Batch Processing, Cloud Engineering, Continuous Integration, Data Architecture, Information Engineering, DevOps, Python (Programming Language), Machine Learning, Software Architecture, Recommender Systems, Standard Sql, Azure Machine Learning, Software Engineering, Data Streaming, Systems Integration, Google Cloud, Feature Engineering, Chatbots, Data Ingestion, Delivery Pipeline, Large Language Models, Backend, Pyspark, Information Technology, Low Latency, Pure Data, Data Analytics, Machine Learning Operations, Data Pipelines, Docker
- **Published:** July 12, 2026
- **Apply:** https://www.careerjet.com/jobad/usdb364a8c5a5b8326bf1e439aa1c78757

## About the Role

* Exceptional software engineering and computer science fundamentals
 * Experience building scalable backend systems supporting ML workloads
 * Ability to architect, deploy, and maintain production-grade AI/ML services
 * Comfort working in ambiguous and evolving environments
 * Strong analytical and systematic problem-solving skills
 * Fast learning ability and intellectual curiosity
 * Experience collaborating cross-functionally with Data Scientists and Engineering teams
 * Proven delivery experience in enterprise or high-scale technology environments, * 5+ years of software engineering experience implementing cloud-native product solutions
 * Strong experience building backend systems supporting ML/algorithmic products
 * Expertise with:

 * Python
 * SQL
 * PySpark
 * Docker
 * Strong AWS cloud experience
 * Experience with Google Cloud Platform (GCP)
 * Experience building streaming and batch data architectures at scale
 * Strong system design and backend architecture experience
 * Experience operating in Agile environments
 * Experience with DevOps and CI/CD practices
 * Ability to handle ambiguity and rapidly changing requirements
 * Strong communication and collaboration skills

Preferred / Nice-to-Have Skills

 * Experience with SageMaker
 * Understanding of feature stores
 * Hospitality or personalization/recommendation system experience
 * Real-time ML inference and personalization systems
 * Infrastructure-as-code implementation experience
 * Experience supporting AI/LLM-enabled applications

 * Team uses existing LLMs rather than building foundational models
 * Master's degree in Computer Science, Software Engineering, or related field

 * Bachelor's degree + strong equivalent experience acceptable

## Description

Candidates with pure data science or research-heavy backgrounds are less aligned unless they possess strong production engineering experience.
Core Responsibilities

 * Design and implement scalable backend architectures supporting machine learning products
 * Build and operationalize AI/ML services across the full product lifecycle:

 * Data ingestion
 * Feature engineering
 * Model integration
 * Real-time inference
 * Batch processing
 * Deployment and monitoring
 * Partner closely with Data Scientists to productionize machine learning models
 * Develop streaming and batch data processing workflows at scale
 * Implement infrastructure-as-code and CI/CD deployment pipelines
 * Enhance and maintain feature store workflows and ML data pipelines
 * Optimize latency, scalability, and reliability of ML systems
 * Build services supporting personalization, recommendation engines, search, analytics, and conversational AI experiences
 * Collaborate with Data Engineering, Architecture, Governance, and Security teams
 * Support cloud-native ML infrastructure within AWS and Google Cloud environments
 * Contribute to system design discussions and technical architecture decisions, * Python
 * SQL
 * PySpark
 * Docker
 * AWS
 * GCP

ML/AI Focus Areas

 * Real-time personalization
 * Recommendation systems
 * Search platforms
 * Internal analytics tooling
 * Chat interfaces and AI-assisted workflows


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