ML Engineer; hybrid

Job Title: AI/ML Engineer - Greenfield AI Project

LOCATION: Irvine, CA (onsite). Monday through Thursday onsite, Fridays remote.

COMPENSATION: $75-95 an hour. This is a 2-year contract that will convert to full-time.

ABOUT US: We are on a mission to develop innovative AI solutions that will revolutionize our workforce. As we embark on an exciting new greenfield AI project, we are seeking an exceptional AI/ML Engineer to join our team and lead the development of machine learning models as part of this groundbreaking initiative.

We are seeking a skilled AI/ML Engineer to join our team to design, develop, and deploy machine learning models that solve real-world business challenges. You will work cross-functionally with data scientists, engineers, and product teams to bring cutting-edge AI solutions to production, with a strong focus on NLP, supervised learning, experimentation, and optimization.

• Model Development & Training
  • Collaborate with data scientists and stakeholders to translate project goals into scalable ML solutions.
  • Design, develop, and train models using state-of-the-art machine learning techniques and tools.
  • Select appropriate annotated datasets and transform raw data into machine learning-ready formats.
• Data Preparation & Feature Engineering
  • Analyze and process structured/unstructured data for training and evaluation.
  • Develop feature extraction and selection pipelines to improve model performance.
• Experimentation & Optimization
  • Run controlled experiments and perform statistical analysis to validate models.
  • Refine model hyperparameters and evaluation metrics for optimal performance.
• Deployment & Integration
  • Work closely with ML Ops to deploy and monitor models in production environments.
  • Ensure all models are integrated seamlessly into existing systems.
• Collaboration & Code Quality
  • Participate in code reviews, pair programming, and knowledge-sharing sessions.
  • Write testable, production-quality code that aligns with engineering best practices.

• 3–5 years as an ML/AI Engineer or 1–3 years in an ML/AI leadership role
• Proven experience building and deploying machine learning models in production
• Solid understanding of classical ML algorithms (classification, regression, clustering)
• Experience working with changing datasets and real-time data pipelines
• Hands‑on experience with Python and frameworks like PyTorch, Tensor Flow, Scikit-learn
• Strong knowledge of data processing (ETL), feature engineering, and statistical evaluation
• Solid understanding of REST APIs, CI/CD, and containerized deployments (Docker, Kubernetes)
• Strong communication, analytical thinking, and problem‑solving skills
• Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related quantitative field

• Master’s or PhD degree in Computer Science, Engineering, or a related field
• Experience with neural networks and deep learning applications in computer vision, time‑series analysis, or reinforcement learning
• Familiarity with MLOps tools (MLflow, Kubeflow, Sage Maker, etc.)
• Exposure to cloud platforms (AWS, GCP, Azure)
• Familiarity with version control and experimentation tracking tools
• Basic knowledge of data governance, security, and compliance standards