Machine Learning Engineer

Quantum Technologies. LLC; Atlanta (GA); Vor Ort; USD 120.000 - 180.000; Vollzeit

Zusammenfassung

Quantum Technologies. LLC is seeking an experienced Machine Learning Engineer to design and deploy scalable ML models for complex business problems in a fast-paced environment.

You will work with large-scale data, build end-to-end ML pipelines, and collaborate across data, product, and engineering teams to deliver production-ready solutions. The role emphasizes model performance optimization, MLOps practices, and governance considerations, with exposure to cloud platforms (AWS/Azure/GCP) and

Qualifikationen

• 6–11 years of ML engineering experience.
• Strong Python proficiency.
• Hands-on with ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
• Experience with data processing frameworks like Spark, Pandas, NumPy.
• Strong understanding of ML algorithms, statistics, and model evaluation.
• Experience deploying models via REST APIs, Docker, Kubernetes.
• Solid knowledge of SQL and working with large databases.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Strong problem-solving and communication skills.

Aufgaben

• Design, develop, and deploy scalable ML models for real-world business problems.
• Work with large-scale structured and unstructured datasets.
• Build and maintain end-to-end ML pipelines (data ingestion, feature engineering, model training, evaluation, deployment).
• Collaborate with Data Engineers, Data Scientists, and Product teams.
• Optimize model performance, accuracy, and efficiency.
• Implement MLOps best practices including monitoring, versioning, retraining.

Kenntnisse

ML engineering

Python

communication

Tools

TensorFlow

PyTorch

Scikit-learn

Spark

Pandas

NumPy

Docker

Kubernetes

SQL

AWS/Azure/GCP

Jobbeschreibung

Manufacturing,Banking & Finance,Retail,Government,Telecom,Oil & Gas,IT/Software

Key Responsibilities

• Design, develop, and deploy scalable Machine Learning models for real-world business problems
• Work with large-scale structured and unstructured datasets
• Build and maintain end-to-end ML pipelines (data ingestion, feature engineering, model training, evaluation, and deployment)
• Collaborate closely with Data Engineers, Data Scientists, and Product teams
• Optimize model performance, accuracy, and efficiency
• Implement MLOps best practices including monitoring, versioning, and retraining
• Ensure compliance with security, governance, and regulatory standards
• Participate in code reviews, design discussions, and technical documentation

Required Skills & Qualifications

• 6–11 years of overall experience with strong focus on Machine Learning Engineering
• Strong programming experience in Python
• Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn
• Experience with data processing frameworks (Spark, Pandas, NumPy)
• Strong understanding of ML algorithms, statistics, and model evaluation techniques
• Experience deploying models using REST APIs, Docker, Kubernetes
• Solid knowledge of SQL and working with large databases
• Experience with cloud platforms (AWS, Azure, or GCP)
• Strong problem-solving and communication skills

Nice to Have

• Prior experience working with financial services or banking clients
• Experience with NLP, Time Series, or Recommendation Systems
• Exposure to CI/CD pipelines and automation tools
• Knowledge of data governance and model risk management

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.