Job Description:
- Client is seeking a broad range of experience levels including; Experienced, Senior, and Subject Matter Expert (SME)/Technical Lead Engineer (TLE) Level DevSecOps Software Engineers who will provide engineering support for a new SW engineering initiative involving AI tools.
- This position will be physically located in Cambridge, MA.
- Designs, develops, documents and implements appropriate and best-fit Artificial Intelligence algorithms and models using standard methods and tools considering ethical implications and potential biases. Uses existing AI tools to analyze their effectiveness in code generation, and application to avionics code. Collects, cleans, preprocesses and analyzes large datasets to ensure data quality, reliability and identifies patterns, trends, and insights. Tests, documents, and debugs Artificial Intelligence models and software systems. Trains, evaluates and optimizes performance and capabilities of Artificial Intelligence models. Conducts Safety Risk Management process for Artificial Intelligence models in accordance with organizational standards. Integrates and deploys efficient and scalable Artificial Intelligence models into production environments. Monitors, validates and improves in-production Artificial Intelligence models. Partners with cross functional teams and domain experts to understand business requirements, gather feedback, and iterate Artificial Intelligence models and algorithms. Researches and implements current and emerging technologies, tools, frameworks, and regulations in the engineering Artificial Intelligence environment and contributes to Artificial Intelligence Design Practice(s).
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- Senior (Level 4)
- • Leads design, development, documentation and implementation of appropriate and best-fit Artificial Intelligence algorithms and models using standard methods and tools considering ethical implications and potential biases.
- • Ability to lead and help junior engineers in accomplishing technical engineering activities.
- • Familiar with automated testing methodologies and frameworks (e.g., Google Test, PyTest) to ensure rapid and efficient test execution.
- • Understanding of CI/CD practices and experience with CI/CD tools (e.g., Jenkins, GitLab CI/CD) to automate and optimize workflows a plus.
- • Ability to collaborate effectively with HIL teams to integrate software with hardware-in-the-loop testing environments a plus.
- • Strong willingness to leverage AI tools and technologies to accelerate software development and testing processes; familiarity with AI frameworks (e.g., TensorFlow, PyTorch) is a plus.
- • Experience in C, C++, Python, or modern coding languages.
- • Familiarity with ADA or avionics software is a plus.
- • Strong team player who enjoys collaboration and the fast-paced startup/high-tech culture.
- • Excellent documentation and communication skills for effective collaboration with cross-functional teams.
Basic Qualifications (Required Skill/Experience):
- • Bachelor's degree and typically 3 or more years' experience in a software engineering classification or a Master's degree with 1 year of experience in a software engineering classification.
- • Must be able to work onsite in Cambridge, MA
- • No relocation offered
- Preferred Qualifications (Desired Skills/Experience):
- • Education or experience in AI Algorithms and/or use of AI Tools
- • Ability to obtain a U.S. Security Clearance if sponsored.
- Typical Education/Experience:
- Senior (Level 4)
- Education/experience typically acquired through advanced technical education from an accredited course of study in engineering, computer science, mathematics, physics or chemistry (e.g. Bachelor) and typically 5 or more years' related work experience or an equivalent combination of technical education and experience (e.g. PhD+1 years' related work experience, Master+3 years' related work experience).
- remote badging will be required
. Skillset Required: Artificial Intelligence algorithms, AI tools, Data collection, Data cleaning, Data preprocessing, Data analysis, Software testing, Debugging, Training AI models, Evaluating AI models, Optimizing AI models, Safety Risk Management, AI model deployment, AI model monitoring, Cross-functional collaboration, Emerging technologies research, AI Design Practice, Automated testing methodologies, Google Test, PyTest, CI/CD practices, Jenkins, GitLab CI/CD, Hardware-in-the-loop testing, AI frameworks, TensorFlow, PyTorch, C, C++, Python, ADA, Avionics software, Documentation, Communication
