

Artificial Intelligence Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for an "Artificial Intelligence Engineer" on a 12-month contract, paying competitively, fully remote. Key skills include Python, AI engineering, advanced algorithms, and containerization tools. Experience with deep learning frameworks and MLOps practices is preferred.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
600
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ποΈ - Date discovered
July 12, 2025
π - Project duration
More than 6 months
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ποΈ - Location type
Remote
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
United States
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π§ - Skills detailed
#Deep Learning #Data Science #Scala #Docker #DevOps #"ETL (Extract #Transform #Load)" #PyTorch #Programming #ML (Machine Learning) #AI (Artificial Intelligence) #Deployment #pydantic #React #TensorFlow #Kubernetes #Python #MLflow #Computer Science
Role description
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AI and Advanced Algorithms Engineer
New York, New York (100% Remote)
12-month Contract
We are seeking an individual to work with a Fortune 50 Broadcast Media & Entertainment leader located in New York, New York. As the AI and Advanced Algorithms Engineer, you will be responsible for developing an innovative AI platform that transforms the creation, curation, and delivery of short-form content. You will have the opportunity to work alongside product managers, engineers, AI specialists, and machine learning experts to build advanced AI systems that shape the future of entertainment. This role is perfect for individuals who excel at the intersection of generative AI, machine learning, and software engineering, with a drive to create impactful AI solutions.
Minimum Qualifications:
β’ Proficiency in Python programming.
β’ Extensive experience with development and deployment tools, including containerization (e.g., Docker, Kubernetes) and workflow orchestration (e.g., Temporal or similar).
β’ Hands-on expertise in applied AI engineering, with a focus on multi-agent systems incorporating advanced reasoning capabilities.
β’ Strong proficiency in advanced algorithms, particularly tree traversal, rebalancing, and navigation over tree structures.
β’ Demonstrated experience with prompt engineering to maximize the capabilities of large language models (LLMs).
β’ Proficiency with agentic workflow tools (e.g., Pydantic, LangGraph, or similar) to support reasoning frameworks like Graph of Thoughts.
Preferred Qualifications:
β’ Experience developing deep learning models using frameworks such as PyTorch or TensorFlow, with an emphasis on reasoning-intensive applications.
β’ Practical experience fine-tuning foundation models to enhance reasoning capabilities, including the integration of Self-Consistency Decoding.
β’ Familiarity with MLOps practices and tools (e.g., MLflow or similar) to streamline the deployment of reasoning-focused multi-agent systems.
β’ Experience with applying Graph of Thoughts for non-linear reasoning and iterative reasoning techniques, such as Reflexion to refine agent decision-making through self-evaluation and feedback mechanisms.
β’ Understanding of ReAct for dynamic decision-making.
Responsibilities:
β’ Design, develop, and deploy sophisticated multi-agent AI systems with advanced reasoning requirements, leveraging state-of-the-art reasoning techniques such as Chain of Thought (CoT), Self-Consistency Decoding, and Reflexion to ensure robust and reliable decision-making.
β’ Implement and optimize tree-based algorithms, including depth-first and breadth-first traversal, rebalancing (e.g., AVL, Red-Black trees), and navigation over tree structures, to efficiently integrate AI outputs into production-ready solutions.
β’ Build and maintain a high-performance computer science infrastructure that utilizes AI results, employing Graph of Thoughts (GoT) to structure non-linear reasoning graphs for seamless integration into scalable, high-performance applications.
β’ Develop and sustain a robust computational framework that transforms AI-generated insights into actionable components, prioritizing performance efficiency and modularity for end-to-end product delivery.
β’ Collaborate with DevOps teams to implement scalable MLOps pipelines, versioning, and deployments using containerization technologies (e.g., Docker, Kubernetes) and workflow orchestration tools.
β’ Work closely with product, data science, engineering, and creative teams to define the technical vision and deliver innovative, impactful solutions.
Whatβs in it for you?
β’ Work with a newly recognized media streaming organization at the forefront of innovation.
β’ Collaborate with high-level business professionals and technical teams, gaining valuable cross-functional experience.
β’ Opportunity to accelerate your career in a fast-paced, evolving industry.