Machine Learning Engineer; Hybrid- Greenfield
Listed on 2026-02-23
-
IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Data Engineer -
Engineering
AI Engineer, Data Engineer
Job Title: AI/ML Engineer - Greenfield AI Project
UNABLE TO OFFER SPONSORSHIP- US CITIZENS & GREEN CARD ONLY
LOCATION: Irvine, CA (onsite). Monday through Thursday onsite, Fridays remote.
SPONSORSHIP NOT AVAILABLE- MUST BE US CITIZEN/ GREEN CARD HOLDER
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.
JOB DESCRIPTION:
About the Role
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.
Key Responsibilities
- 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.
Qualifications & Skills
- 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
Preferred Qualifications (Nice‑to‑Have)
- 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
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