Machine Learning Software Engineer
Solidus, Columbia, MD
Solidus is looking for a Software Engineer with 10 years+ experience in programming machine systems to develop applications to reduce the strain and peripheralworkload on the human analyst through the use of machine learning techniques which reduce the amount of data through which an analyst must sift. This may include collecting, correlating, analyzing, and triaging large amount of data on a constant basis.
REQUIREMENTS
- TS/SCI with FSP (optimum) or CI Poly
- Bachelor's degree in Computer Science or related discipline
- A minimum of 20 years' experienceas a software engineer in related programs
Experience in the following:
- 10 years of experience programming in multiple languages
- 5 years of experience developing and programming in multiple environments
- Sequential decision making- Reinforcement learning
- Single agent and multi-agent planning
- "Closed-loop" decision making systems that interact with the environment to obtain useful information
- Automated control systems and implementing mechanisms
- One or more of the following: game theory,control theory, operations research, information theory, simulation-based optimization, multi-agent systems, swarm intelligence,statistics, and genetic algorithms.
Solidus, Columbia, MD
Solidus is looking for a Software Engineer with 10 years+ experience in programming machine systems to develop applications to reduce the strain and peripheralworkload on the human analyst through the use of machine learning techniques which reduce the amount of data through which an analyst must sift. This may include collecting, correlating, analyzing, and triaging large amount of data on a constant basis.
REQUIREMENTS
- TS/SCI with FSP (optimum) or CI Poly
- Bachelor's degree in Computer Science or related discipline
- A minimum of 20 years' experienceas a software engineer in related programs
Experience in the following:
- 10 years of experience programming in multiple languages
- 5 years of experience developing and programming in multiple environments
- Sequential decision making- Reinforcement learning
- Single agent and multi-agent planning
- "Closed-loop" decision making systems that interact with the environment to obtain useful information
- Automated control systems and implementing mechanisms
- One or more of the following: game theory,control theory, operations research, information theory, simulation-based optimization, multi-agent systems, swarm intelligence,statistics, and genetic algorithms.
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