ML Engineer

Job Title: ML Engineer

Location: Sunrise FL

Work Type: Hybrid

Employment Type: Contract (C2C)

Work Authorization: Only US Citizens / GC Holders

About the Role:

We are seeking an experienced Machine Learning Engineer to join our team on a contract basis. The ideal candidate should have strong expertise in Python development hands-on experience building and deploying machine learning models and proven ability to operationalize ML solutions through APIs on Google Cloud Platform (GCP). This role requires end-to-end ownership of ML systems from data preparation and model development to deployment monitoring and integration into production environments.

Key Responsibilities:

• Design develop and maintain machine learning models using Python
  
• Perform data preprocessing feature engineering model training evaluation and optimization
  
• Build and manage end-to-end ML pipelines including training validation deployment and monitoring
  
• Develop deploy and maintain RESTful APIs and Python-based microservices to serve ML models
  
• Integrate ML solutions into enterprise applications and workflows
  
• Deploy and manage ML workloads on Google Cloud Platform (GCP)
  
• Utilize GCP services such as Vertex AI Cloud Run Cloud Functions BigQuery and Cloud Storage
  
• Ensure scalability performance reliability and security of deployed solutions
  
• Collaborate with cross-functional teams including product data and engineering
  
• Troubleshoot and resolve issues across the ML and application stack
  
  

Required Skills & Qualifications:

• Bachelors degree in Computer Science Engineering or a related field (or equivalent experience)
  
• 37 years of experience as a Machine Learning Engineer or Python Backend Engineer
  
• Strong proficiency in Python with ability to write clean optimized production-quality code
  
• Hands-on experience with ML libraries such as NumPy Pandas Scikit-learn
  
• Experience building training and deploying machine learning models
  
• Strong understanding of the machine learning lifecycle and pipelines
  
• Experience developing RESTful APIs or microservices using FastAPI Flask or similar frameworks
  
• Practical experience deploying applications and ML models on Google Cloud Platform (GCP)
  
• Familiarity with version control systems (Git)
  
• Strong problem-solving debugging and communication skills
  
  

Preferred Skills:

• Experience with PyTorch or TensorFlow
  
• Exposure to Generative AI Large Language Models (LLMs)
  
• Hands-on experience with LangChain LangGraph or similar AI frameworks
  
• Familiarity with AI agent architectures and modern ML frameworks
  
• Experience with cloud-native architectures containerization and CI/CD pipelines
  
• Knowledge of vector databases and ML model monitoring tools