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Johns Hopkins Applied Physics Laboratory
Laurel, Maryland
Source: Johns Hopkins Applied Physics Laboratory careers · View original posting
From Johns Hopkins Applied Physics Laboratory's posting. “We” and “our” refer to the employer.
Description
Are you passionate about applying hands-on expertise to build and deliver artificial intelligence and machine learning solutions?
Are you looking to tackle a wide range of complex problems in a field that is evolving faster than almost any other in technology?
Do you have a strong desire to collaborate and work within a team of highly skilled researchers?
If so, we're looking for someone like you to join our team at APL!
We are seeking a highly motivated AI/ML platform engineer who will contribute to solving cutting edge challenges that didn’t exist until recently — integrating agents with enterprise tools, fine-tuning models for regulated use cases, and building the operational discipline that keeps AI systems reliable as the underlying technology changes monthly. You will be joining a team of engineers and scientists who are at the forefront of APL's mission to provide innovative solutions to critical challenges in the area of missile defense.
As an AI/ML Platform Engineer...
You will work at the intersection of software engineering, data science, and machine learning, to turn experimental models into scalable, operation-ready solutions.
You will design and build multi-agent and single-agent systems using modern open-source frameworks (e.g.: LangChain/LangGraph, CrewAI, AutoGen, and their successors) that automate and augment work across our enterprise and developer tools.
You will fine-tune LLMs for specific applications using modern techniques (e.g.: LoRA). Prepare training data, run training jobs on shared infrastructure, evaluate results against task-specific benchmarks, and hand off to the ML team's serving platform.
You will research and prototype ML algorithms for specific production tasks, measure their performance and limitations rigorously, and produce clear assessments of their robustness and the confidence we can place in them.
You will interact with various data types, formats, and structures in a clear and appropriate manner for algorithm training and testing and perform any data cleaning, normalization, or manipulation as needed.
You will create effective visualizations and comprehensive documentation to explain complex topics to a variety of audiences.
Why Work at APL?
The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation’s most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.
At APL, we celebrate our differences of perspectives and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL’s campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at https://www.jhuapl.edu/careers.
All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law. APL is committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities.
If you require a reasonable accommodation to participate in any part of the hiring process, please contact
Accessibility@jhuapl.edu.
The referenced pay range is based on JHU APL’s good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation.
Additional compensation may be provided in the form of a sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis.
Minimum Rate
$85,000 Annually
Maximum Rate
$195,000 Annually
We are seeking a highly motivated AI/ML platform engineer who will contribute to solving cutting edge challenges that didn’t exist until recently — integrating agents with enterprise tools, fine-tuning models for regulated use cases, and building the operational discipline that keeps AI systems reliable as the underlying technology changes monthly. You will be joining a team of engineers and scientists who are at the forefront of APL's mission to provide innovative solutions to critical challenges in the area of missile defense.
As an AI/ML Platform Engineer...
You will work at the intersection of software engineering, data science, and machine learning, to turn experimental models into scalable, operation-ready solutions.
You will design and build multi-agent and single-agent systems using modern open-source frameworks (e.g.: LangChain/LangGraph, CrewAI, AutoGen, and their successors) that automate and augment work across our enterprise and developer tools.
You will fine-tune LLMs for specific applications using modern techniques (e.g.: LoRA). Prepare training data, run training jobs on shared infrastructure, evaluate results against task-specific benchmarks, and hand off to the ML team's serving platform.
You will research and prototype ML algorithms for specific production tasks, measure their performance and limitations rigorously, and produce clear assessments of their robustness and the confidence we can place in them.
You will interact with various data types, formats, and structures in a clear and appropriate manner for algorithm training and testing and perform any data cleaning, normalization, or manipulation as needed.
You will create effective visualizations and comprehensive documentation to explain complex topics to a variety of audiences.
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