AI Engineer
JPS Tech SolutionsContract
Required Skillset:
PythonPandasMicroservicesScikit-learnAzureDockerKubernetesAWSGCPFastAPICI/CD pipelinesRESTful APIsTensorFlowNumPyPyTorchMLOpsModel monitoring
Job Description
Role: AI Engineer - W2
Experience: 12+ Years
Duration: 6+ Months
Location: Remote
Role Overview:
We are seeking a highly experienced AI Engineer to design, develop, and deploy scalable AI and machine learning solutions in production environments. The ideal candidate will have a strong background in building intelligent systems, optimizing models, and integrating AI capabilities into enterprise applications.
Key Responsibilities:
- Design, develop, and deploy machine learning and deep learning models for real-world business use cases
- Build and maintain scalable data pipelines and AI-driven microservices using Python
- Implement model training, evaluation, tuning, and performance optimization techniques
- Integrate AI/ML solutions into enterprise applications through APIs and cloud platforms
- Support MLOps practices including CI/CD pipelines, deployment automation, and production monitoring
- Ensure model reliability, scalability, and performance in production environments
- Collaborate with engineering, data, and business teams to translate requirements into AI solutions
Required Skills & Experience:
- 12+ years of overall experience in software engineering, AI, or machine learning
- Strong expertise in Python, including NumPy, Pandas, and FastAPI
- Hands-on experience with machine learning and deep learning frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Proven experience deploying and maintaining ML models in production environments
- Strong understanding of cloud platforms such as AWS, Azure, or GCP
- Experience with Docker, Kubernetes, and containerized deployments
- Solid knowledge of RESTful APIs and microservices architecture
- Experience with MLOps, CI/CD pipelines, and model monitoring
Preferred Skills:
- Experience with NLP, Large Language Models (LLMs), or Generative AI
- Familiarity with enterprise-scale, distributed systems and data platforms
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