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Machine Learning Engineer; Hybrid- Greenfield

Job in Los Angeles, Los Angeles County, California, 90079, USA
Listing for: Match Made Tech
Full Time, Contract position
Listed on 2026-02-16
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 75 - 95 USD Hourly USD 75.00 95.00 HOUR
Job Description & How to Apply Below
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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