SSi People
Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with 3–5 years of experience in ML infrastructure using Python, AWS services, and real-time data streaming. Requires expertise in TensorFlow, PyTorch, SQL, and familiarity with Kubeflow. Contract length and pay rate unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
October 16, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Remote
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
New York City Metropolitan Area
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🧠 - Skills detailed
#S3 (Amazon Simple Storage Service) #Data Science #SQL (Structured Query Language) #AWS Kinesis #Data Storage #TensorFlow #Python #AWS (Amazon Web Services) #Debugging #PyTorch #Data Processing #Data Engineering #ML (Machine Learning) #EC2 #Storage #Lambda (AWS Lambda)
Role description
W2 ONLY - we are not able to provide sponsorship
REMOTE
Requirements
• 3–5 years of hands-on experience implementing production ML infrastructure at scale using Python
• Experience with AWS services (e.g., EC2, S3, Lambda)
• Familiarity with real-time data streaming platforms like AWS Kinesis and Google Pub/Sub
• Exposure to Kubeflow (local environment experience is acceptable)
• Strong grasp of core ML and data science concepts
• Ability to explain SQL operations (e.g., inner/outer joins)
• Understanding of data storage formats (e.g., columnar vs row-based)
• Familiarity with distributed data processing techniques such as MapReduce
• Able to describe and compare runtime complexity of different operations
• Writes clean, idiomatic Python code with the ability to explain solutions, alternatives, and performance tradeoffs
• Solid debugging skills (expert-level not required)
• Experience with TensorFlow and PyTorch is required
• Familiarity with Kubeflow and Ray is strongly preferred
W2 ONLY - we are not able to provide sponsorship
REMOTE
Requirements
• 3–5 years of hands-on experience implementing production ML infrastructure at scale using Python
• Experience with AWS services (e.g., EC2, S3, Lambda)
• Familiarity with real-time data streaming platforms like AWS Kinesis and Google Pub/Sub
• Exposure to Kubeflow (local environment experience is acceptable)
• Strong grasp of core ML and data science concepts
• Ability to explain SQL operations (e.g., inner/outer joins)
• Understanding of data storage formats (e.g., columnar vs row-based)
• Familiarity with distributed data processing techniques such as MapReduce
• Able to describe and compare runtime complexity of different operations
• Writes clean, idiomatic Python code with the ability to explain solutions, alternatives, and performance tradeoffs
• Solid debugging skills (expert-level not required)
• Experience with TensorFlow and PyTorch is required
• Familiarity with Kubeflow and Ray is strongly preferred
