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Machine Learning Process Engineer Jobs (NOW HIRING)

We are looking for a Machine Learning Engineer to design, build, and deploy machine learning systems that improve the calibration, control, and operation of quantum processors. In this role, you will ...

... processing (NLP) create and implement machine learning models and algorithms. • Automate the deployment and monitoring of AI models, collaborate with DevOps teams. • Use AI to automate processes ...

As a Machine Learning Engineer, you will work within a collaborative technical team to build ... industrial, process, plant, or production data.- A GitHub portfolio or other examples that ...

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Machine Learning Process Engineer information

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How much do machine learning process engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for machine learning process engineer in the United States is $92,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,500.00 and $103,000.00 per year, depending on experience, location, and employer.

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Infographic showing various Machine Learning Process Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, 3% Contract, and 1% Nights. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $92,018 per year, or $44.2 per hour.

Machine Learning Engineer

Honolulu, HI • On-site

Cymertek Corporation
IT Services • 11 - 50 employees

Full-time

Re-posted 7 days ago


Job description

Job Summary:
Cymertek Corporation is seeking a talented and innovative Machine Learning Engineer to join their team and help build intelligent systems that drive impactful business solutions. In this role, you will design, develop, and deploy machine learning models to solve complex problems and improve decision-making processes while collaborating with data scientists, engineers, and product teams.
Responsibilities:
• Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning)
• Ability to design, implement, and optimize machine learning models and workflows
• Experience working with large, complex datasets
• Knowledge of data preprocessing and feature engineering
• Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure)
• Strong problem-solving skills and analytical thinking
Qualifications:
Required:
• TS/SCI Full Poly (Please note this position requires full U.S. Citizenship)
• Bachelor's Degree
• Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning)
• Ability to design, implement, and optimize machine learning models and workflows
• Experience working with large, complex datasets
• Knowledge of data preprocessing and feature engineering
• Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure)
• Strong problem-solving skills and analytical thinking
• Proficiency in programming languages (e.g., Python, R, Java)
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
• Expertise in model evaluation techniques and metrics
• Strong knowledge of version control tools (e.g., Git)
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau)
• Understanding of database technologies (e.g., SQL, NoSQL)
Preferred:
• Experience with natural language processing (NLP)
• Knowledge of deep learning techniques (e.g., CNNs, RNNs)
• Familiarity with deployment tools (e.g., Docker, Kubernetes)
• Experience with data augmentation and synthetic data generation
• Ability to collaborate in cross-functional teams (e.g., engineers, product managers)
• Knowledge of edge computing and model optimization for deployment
Company:
With headquarters in Maryland, Cymertek [/'sī-mer-tek/] Corporation provides superior consulting services for the implementation of high quality information systems. Founded in 2010, the company is headquartered in Laurel, USA, with a team of 11-50 employees. The company is currently Early Stage.