

Innovatech Staffing
Data Engineer(W2 Only)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer (W2 Only) with a contract length of "unknown" and a pay rate of "unknown." Required skills include 5-8 years in Machine Learning Engineering, 3 years designing ETL pipelines with AWS, and proficiency in Python.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
June 24, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Unknown
-
📄 - Contract
W2 Contractor
-
🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#Data Pipeline #Documentation #R #Libraries #Data Engineering #Programming #Datasets #Scala #Python #AI (Artificial Intelligence) #Monitoring #ML (Machine Learning) #Deep Learning #Data Science #"ETL (Extract #Transform #Load)" #API (Application Programming Interface) #Security #Spark (Apache Spark) #Cloud #Data Lineage #PySpark #AWS (Amazon Web Services) #Data Exploration
Role description
Responsibilities
• We are seeking an experienced Machine Learning Engineer to join our AI/ML Engineering team. You will be responsible for developing and optimizing complex data pipelines, integrating model pipelines, and building scalable AI/ML solutions, including large language models (LLMs). The ideal candidate will possess a robust background in traditional machine learning, deep learning, and significant experience with large datasets and cloud-based AI services
• .Develop and optimize complex data pipelines, applying machine learning engineering principles to enhance efficiency and scalability
• .Integrate and optimize data and model pipelines within production environments, diagnosing data inconsistencies and documenting assumptions
• .Collaborate with data science teams to review model-ready datasets and feature documentation, ensuring completeness and accuracy
• .Perform data discovery and analysis of raw data sources, applying business context to meet model development needs
• .Comfort with exploratory data exploration and tracking data lineage during inception or root cause analysis
• .Write and maintain model monitoring scripts, diagnosing issues and coordinating resolutions based on alerts
.Qualification
s
Around 5-8 years of relevant work experience (Machine Learning Engineering
).
At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMake
r).
Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and framewo
rks.
Robust understanding of cloud technologies, including AWS and A
zure.
Experience with API design and development is a
plus.
Solid understanding of software engineering principles, including design patterns, testing, security, and version c
ontrol.
Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Eva
luation.
Responsibilities
• We are seeking an experienced Machine Learning Engineer to join our AI/ML Engineering team. You will be responsible for developing and optimizing complex data pipelines, integrating model pipelines, and building scalable AI/ML solutions, including large language models (LLMs). The ideal candidate will possess a robust background in traditional machine learning, deep learning, and significant experience with large datasets and cloud-based AI services
• .Develop and optimize complex data pipelines, applying machine learning engineering principles to enhance efficiency and scalability
• .Integrate and optimize data and model pipelines within production environments, diagnosing data inconsistencies and documenting assumptions
• .Collaborate with data science teams to review model-ready datasets and feature documentation, ensuring completeness and accuracy
• .Perform data discovery and analysis of raw data sources, applying business context to meet model development needs
• .Comfort with exploratory data exploration and tracking data lineage during inception or root cause analysis
• .Write and maintain model monitoring scripts, diagnosing issues and coordinating resolutions based on alerts
.Qualification
s
Around 5-8 years of relevant work experience (Machine Learning Engineering
).
At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMake
r).
Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and framewo
rks.
Robust understanding of cloud technologies, including AWS and A
zure.
Experience with API design and development is a
plus.
Solid understanding of software engineering principles, including design patterns, testing, security, and version c
ontrol.
Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Eva
luation.






