Crossing Hurdles

Machine Learning Engineer | Remote

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer, remote, with a contract duration of over 6 months and a pay rate of $160K - $300K/yr. Key skills include Python, AWS, FastAPI, and LangChain; an advanced degree in math or related fields is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
1363
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🗓️ - Date
July 7, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#AWS (Amazon Web Services) #Microservices #AI (Artificial Intelligence) #ML (Machine Learning) #Documentation #FastAPI #Langchain #Scala #Statistics #Python #Cloud
Role description
Position: Member of Technical Staff, AI/ML Engineering Type: Full-time Compensation: $160K - $300K/yr Location: Remote Commitment: 10-40 hrs/week Role Responsibilities • Design, build, and deploy AI/ML solutions with a focus on large language models (LLMs) using Python and AWS infrastructure. • Architect scalable APIs and microservices utilizing FastAPI, ensuring robust, high-performance systems. • Integrate LangChain and advanced AI frameworks to deliver innovative model interaction capabilities. • Collaborate with cross-functional teams to translate complex mathematical, statistical, or physics-based problem statements into actionable engineering solutions. • Apply core math, statistics, or physics knowledge to improve model performance, interpretability, and reliability. • Maintain high standards of code quality, documentation, and peer reviews within a fast-paced core team. Requirements • Advanced degree or demonstrable expertise in math, quantitative sciences, statistics, or physics. • Expert proficiency in Python for AI/ML engineering. • Hands-on experience deploying, fine-tuning, and integrating LLMs. • Strong background in AWS services and cloud-native ML workflows. • Proven track record using LangChain for chaining LLMs and orchestrating multi-step reasoning. • Solid understanding of FastAPI for building scalable APIs. Application Process • Easy Apply on LinkedIn • Check email for next steps • Participate in resume evaluation & interview stage