Machine Learning Data Engineer

EdgeQ Technologies Private Limited; United States; Remote; USD 110,000 - 175,000; Full time

Job summary

EdgeQ Technologies Private Limited in the United States is seeking a Machine Learning Data Engineer to design and maintain scalable data pipelines and data infrastructure supporting ML applications.

You will work with Data Scientists and ML engineers to prepare high-quality training data, implement preprocessing and feature extraction, and optimize cloud-based pipelines for performance and governance.

Qualifications

• 3–8 years of professional experience in Data Engineering or ML data engineering.
• Strong programming skills in Python and SQL.
• Hands-on experience building ETL/ELT pipelines.
• Experience with distributed processing frameworks (Spark/PySpark).
• Knowledge of cloud data platforms and data warehouses.

Responsibilities

• Design, develop, and maintain scalable data pipelines for ML/AI applications.
• Build and optimize ETL/ELT workflows for structured and unstructured datasets.
• Develop data ingestion, transformation, validation, and processing solutions.
• Collaborate with Data Scientists, ML Engineers, and AI teams to prepare training datasets.
• Implement data preprocessing, feature engineering, and feature extraction pipelines.
• Manage large-scale datasets using distributed processing technologies.
• Develop and maintain cloud-based data infrastructure.
• Implement data quality checks, monitoring, and automated validation processes.
• Optimize data storage, retrieval, and processing performance.
• Support machine learning model training, evaluation, and deployment workflows.
• Integrate data from APIs, databases, streaming platforms, and external sources.
• Implement data governance, security, and compliance best practices.
• Maintain technical documentation and participate in code reviews.

Skills

Python

SQL

ETL/ELT pipelines

Apache Spark

Airflow

AWS/Azure/GCP

Data modeling

Git CI/CD

Kubernetes

Education

Bachelor's or Master's degree in CS/DS/IT/Engineering

Tools

Snowflake

BigQuery

Redshift

Databricks

Kafka

Docker

Kubernetes

Delta Lake

Dagster

MLflow

Job description

Headquarters: United States

Machine Learning Data Engineer Job Title: Machine Learning Data EngineerLocation: United States (Remote)Work Mode: 100% RemoteExperience: 3–8 YearsSalary Range: $110,000 – $175,000 per year (USD)Employment Type: Full-TimeJob Category: Artificial Intelligence / Machine Learning / Data Engineering

Job Summary We are seeking a skilled and experienced Machine Learning Data Engineer to join our growing AI and Data Engineering team in the United States. The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines, data infrastructure, and data processing systems that support machine learning and artificial intelligence applications.

The candidate should have strong expertise in Python, SQL, ETL/ELT pipelines, cloud data platforms, big data technologies, and machine learning data workflows.

This position offers a fully remote work opportunity for qualified candidates across the United States.

Key Responsibilities Design, develop, and maintain scalable data pipelines for machine learning and AI applications.

Build and optimize ETL/ELT workflows for structured and unstructured datasets.

Develop data ingestion, transformation, validation, and processing solutions.

Collaborate with Data Scientists, ML Engineers, and AI teams to prepare high-quality training datasets.

Implement data preprocessing, feature engineering, and feature extraction pipelines.

Manage large-scale datasets using distributed processing technologies.

Develop and maintain cloud-based data infrastructure.

Implement data quality checks, monitoring, and automated validation processes.

Optimize data storage, retrieval, and processing performance.

Support machine learning model training, evaluation, and deployment workflows.

Integrate data from APIs, databases, streaming platforms, and external sources.

Implement data governance, security, and compliance best practices.

Maintain technical documentation and participate in code reviews.

Required Skills & Qualifications 3–8 years of professional experience in Data Engineering, Machine Learning Data Engineering, or related roles.

Strong programming skills in Python and SQL.

Hands-on experience building ETL/ELT pipelines.

Experience with Apache Spark, PySpark, or similar distributed processing frameworks.

Strong knowledge of relational and NoSQL databases.

Experience with AWS, Microsoft Azure, or Google Cloud Platform.

Familiarity with data warehouses such as Snowflake, BigQuery, Redshift, or Databricks.

Experience with Apache Airflow, Dagster, or similar workflow orchestration tools.

Understanding of machine learning data preparation and feature engineering.

Knowledge of data modeling, data lakes, and lakehouse architectures.

Experience with Git, CI/CD, and automated testing.

Strong analytical, debugging, and problem-solving skills.

Preferred Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, Engineering, or a related field.

Experience with MLflow, Kubeflow, Feast, or other MLOps and feature store technologies.

Familiarity with TensorFlow, PyTorch, or Scikit-learn.

Experience with Apache Kafka or real-time streaming pipelines.

Knowledge of Delta Lake, Apache Iceberg, or Apache Hudi.

Experience supporting Generative AI and LLM data pipelines.

Familiarity with vector databases such as Pinecone, Weaviate, or Milvus.

Knowledge of Docker, Kubernetes, and infrastructure automation.

Experience with data governance, lineage, and privacy frameworks.

Salary & Benefits Annual Salary: $110,000 – $175,000 USD (Indicative range based on experience and technical expertise).

Competitive compensation and performance-based incentives, where applicable.

100% remote work opportunity.

Flexible working arrangements.

Health, dental, and vision insurance.

Paid time off and holidays.

Retirement savings benefits, where applicable.

Professional development and technical certification support.

Career growth and advancement opportunities.

Work Location United States – Fully Remote

Candidates from eligible locations across the United States are encouraged to apply.

Applicants must be legally authorized to work in the United States.

Ability to collaborate with distributed teams across different US time zones.

Occasional virtual meetings and collaboration with engineering stakeholders may be required.

Equal Opportunity Employer: We welcome qualified candidates from diverse professional backgrounds and encourage applications from eligible candidates across the United States.