Python AI Engineer

🔎 Python AI Engineer | Lorven Technologies | New York, USA

🏢 Recruiting Company:
Lorven Technologies
🌍

Job Location:

New York, USA
💼 Job Type: Contract
📧 Application Method:

Lorven Technologies is seeking a talented Python AI Engineer to support the development, deployment, and optimization of AI-driven applications. This role is essential to building scalable machine learning solutions and delivering production-ready APIs for real-world business use cases.

As a Python AI Engineer, you will work closely with cross-functional teams to design, train, and integrate machine learning models into robust backend systems. You will develop clean, efficient Python code, implement APIs, and collaborate on model evaluations and refinements. The role offers the opportunity to work with modern ML frameworks, contribute to cutting‑edge AI features, and ensure smooth end‑to‑end deployment.

You will thrive in an environment that values innovation, performance, and high coding standards.

• Develop and maintain Python-based AI/ML components and services
• Build and deploy APIs using FastAPI or Flask for ML model integration
• Implement machine learning models using PyTorch, Tensor Flow, or scikit‑learn
• Conduct model evaluations, tuning, and performance optimization
• Collaborate with engineering teams to package, test, and deploy ML solutions
• Write clean, modular, well-tested Python code (OOP and async fundamentals)
• Support end‑to‑end ML pipeline development and documentation

• Strong Python expertise, including OOP, async basics, packaging, and testing
• Solid understanding of supervised & unsupervised learning fundamentals
• Knowledge of model evaluation techniques and bias‑variance trade‑offs
• Hands‑on experience with PyTorch, Tensor Flow, or scikit‑learn
• Experience building APIs using FastAPI or Flask
• Ability to build scalable, production‑ready AI systems
• Strong debugging, problem‑solving, and analytical skills

• Experience with containerization (Docker) or cloud platforms (AWS/GCP)
• Familiarity with CI/CD pipelines for ML
• Exposure to vector databases or embeddings
• Knowledge of MLOps tools (MLflow, Kubeflow, Weights & Biases)
• Experience with data preprocessing, feature engineering, or model monitoring

Showcase Git Hub or portfolio examples of ML models deployed via APIs—real‑world, runnable demos help you stand out instantly and demonstrate your end‑to‑end engineering capability.