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ML Engineer

Job in Charlotte, Mecklenburg County, North Carolina, 28296, USA
Listing for: SRI Tech
Full Time, Part Time position
Listed on 2026-10-12
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist, Data Analyst
Salary/Wage Range or Industry Benchmark: 59 - 60 USD Hourly USD 59.00 60.00 HOUR
Job Description & How to Apply Below
Job :
Charlotte , NCSalary: USD 59-60 / Hourly (C2C)

Employment Type:

C2C, Full Time Company: SRI Tech Solutions

Job Title:

ML Engineer

Location:

Charlotte , NC (hybrid 2 days a week)
JD:

Advanced degree (Master's or Ph.D.) in Computer Science, Statistics, Mathematics, Economics, or related field.

Proven experience in data science, machine learning, or predictive analytics roles

Proficiency in programming languages commonly used in data science (e.g., Python, R, etc.)Experienced in using AI/ML platforms, technologies, techniques (e.g. Tensor Flow, PyTorch, scikit-learn, NLP, LLM, GenAT)
Design and conduct experiments to test hypotheses and validate model assumptions

Analyze experimental results and provide recommendations for further optimization.

Implement clustering, classification, regression, and other machine learning algorithms as needed.

Apply data mining techniques to extract actionable insights from structured and unstructured data.

Identify patterns and anomalies in data to detect fraud, predict customer behavior, or optimize business processes.

Develop and deploy predictive models using machine learning algorithms

Perform feature engineering, model selection, and hyperparameter tuning to optimize model performance.

Evaluate model accuracy, precision, recall, and other performance metrics

Collaborate with cross-functional teams, including engineers, product managers, and business stakeholdersSRI Tech Solutions is an equal opportunity employer and does not discriminate on the basis of race, color, gender, religion, age, sexual orientation, national origin or citizenship status or ethnic origin, disability, marital status, veteran status, or any other occupationally irrelevant criteria.
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