Machine Learning Engineer Jobs in Winchester, VA (12)
Plant Manager
Software Engineer, Machine Learning
Machine Learning Engineer
Machine Learning Engineer
Administrative/Data Entry Clerk
Finance Administrator
Finance and Logistics Administrator
Mobile Mechanic
Automation Test Engineer
Sr Business Development Specialist - Automotive Artificial Leather
Software Engineering Lead
Unified Communications Engineer- Tier 3- Clearance Sponsorship
Land Surveyor (Party Chief to Sr PLS)
Oracle APEX Developer
Construction Inspector
Job Description
Working as a Machine Learning Engineer in Winchester, VA
There are 12 Machine Learning Engineer opportunities available in Winchester, VA all with unique requirements.
Machine Learning Engineers use automation and algorithms to optimize operations, maximize the efficiency of business processes. Responsibilities include designing, developing, and implementing systems using machine learning models such as neural networks, Bayesian networks, decision trees, support vector machines, and Hidden Markov Models. They use their programming skills to introduce logic into decision-making processes. These systems are used to improve manufacturing output; product development processes; logistical processes; communications; fraud detection; loan underwriting; credit risk prediction; medical diagnosis and treatment selection; security screening of subjects such as prisoners or immigrants seeking access to sensitive areas such as airports or courtrooms.
Machine Learning Engineer jobs near Winchester, VA
Machine Learning Engineers in Winchester, VA Resume Data
Average Experience for Machine Learning Engineers in Winchester, VA
- More than 10 years: 75%
- 6-10 years: 19%
- 3-5 years: 6%
Educational Background for Machine Learning Engineers in Winchester, VA
- Bachelors: 54%
- Masters: 31%
- Doctorate: 8%
- Diploma: 8%
Top Skill for Machine Learning Engineers in Winchester, VA
- Construction safety: 14%
- Analyzing data: 14%
- Attention to detail: 14%
- Basic maintenance and repair: 14%
- Mechanical knowledge: 14%
- Mechanical skills: Monitoring: 14%
- Work style: Conscientiousness: 14%
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