

Senior Machine Learning Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Machine Learning Engineer with a 6+ month contract in Reston, VA (Hybrid). Requires 10+ years in application development, 5+ years in cloud (AWS/Azure), and expertise in AI/ML solutions. Preferred qualifications include a master’s degree and relevant certifications.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
July 24, 2025
🕒 - Project duration
More than 6 months
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🏝️ - Location type
Hybrid
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📄 - Contract type
W2 Contractor
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Reston, VA
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🧠 - Skills detailed
#Spark (Apache Spark) #Python #DataOps #Cloud #R #AI (Artificial Intelligence) #Azure #Leadership #ML (Machine Learning) #Computer Science #Programming #AWS (Amazon Web Services)
Role description
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Hiring for Financial Services Client
Job Position: AI/ML Architect
Job Type: W2/C2C
Location: Reston VA (Hybrid - 3x a week from day 1)
Duration: 6+ month Contract
Qualifications:
• Should have a bachelor’s degree in Computer Science or related field.
• Master’s degree is preferred or equivalent Desired Experiences.
• 10 plus years of progressive hands-on experience in application development with 5 to 6 years of solution architecture, systems architecture and engineering, analysis and applications programming in AI related discipline.
• Technical team leadership role is preferred.
• A minimum of 5 years’ experience in working with a cloud provider (AWS or Azure).
• Experience with Architecture principles and TOGAF framework is a plus.
• AI/ML relevant AWS Professional Certification is preferred.
Required Skills:
• Proven track record of implementing machine learning solutions, AI services and statistical analysis related projects in production.
• Technical leadership with analytical, problem solving and communication skills.
• Familiarity with cloud AI/ML platform offerings, features.
• Understanding of AI services for speech, vision and text.
• Machine learning background with algorithms.
• Expertise in MLOps and dataops lifecycles and engineering implementation in enterprise.
• Ability to code in Python, Spark or R as a programming language.