Machine Learning Engineer; Hybrid- Greenfield

Position: Machine Learning Engineer (Hybrid- Greenfield Opportunity)
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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