AI Engineer (Associate) - Remote

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💎 Seniority level: Middle, 4 years

📍 Location: United States, Canada

💸 Salary: 100000.0 - 125000.0 USD per year

🏢 Company: huroncareers

🗣️ Languages: English

⏳ Experience: 4 years

🪄 Skills: AWSBackend DevelopmentDockerPythonSoftware DevelopmentSQLCloud ComputingData AnalysisFlaskFrontend DevelopmentKubernetesMachine LearningPyTorchAlgorithmsAPI testingAzureData engineeringData scienceFastAPITensorflowCommunication SkillsAnalytical SkillsCI/CDProblem SolvingRESTful APIsAdaptabilityTeamworkJSONData modelingData managementDebugging

Requirements:

Minimum of 4 years of hands-on experience in AI/ML development or intelligent application engineering
Proficiency in Python and familiarity with modern ML/AI libraries (e.g., scikit-learn, PyTorch, TensorFlow, OpenAI APIs)
Experience building APIs or backend services using FastAPI, Flask, or equivalent frameworks
Exposure to agent frameworks (e.g., LangGraph, AutoGen) and vector databases
Familiarity with cloud platforms (Azure, AWS) and containerization tools (Docker)
Familiarity with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or Google AI/ML services
Experience with MLOps pipelines, CI/CD for model delivery, or model monitoring is a plus
Familiarity with orchestration standards or tools such as MCP or agent routing protocols is a plus
Knowledge of AI system evaluation, observability, or prompt performance testing is a plus
Ability to work on cross-functional teams, balance multiple projects, and communicate effectively with technical and non-technical audiences
Cloud certifications in AI/ML services (Azure, AWS, or Google Cloud) is a plus
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field

Responsibilities:

Design and develop AI-powered systems using both traditional ML and generative AI techniques, including prompt engineering, fine-tuning, and embeddings
Build intelligent applications and agents that can perform tasks autonomously or interactively, using frameworks like LangGraph, AutoGen, CrewAI or similar
Create modular, well-documented APIs and service components (e.g., using FastAPI or Flask) to enable model integration and consumption
Develop and manage data pipelines, including data collection, transformation, and quality assurance to support model training
Implement observability and evaluation mechanisms to monitor AI system behavior, including accuracy, drift, reliability, and task-level reasoning
Collaborate with software engineers, data scientists, and solution architects to ensure seamless design, development, and transition to production
Support rapid experimentation as well as robust deployment pipelines, depending on the maturity of each use case
Stay informed on the latest trends in GenAI, AI agents, orchestration protocols, and evaluation frameworks to continuously evolve our capabilities

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