2024 Graduate - AI Solutions Engineering - Johns Hopkins Applied Physics Laboratory

Description:

Do you thrive in a fast-paced, dynamic environment? Do you have a passion for artificial intelligence (AI) and machine learning (ML) systems? Are you a continuous learner, organized, and enjoy working in a collaborative team environment? Are you ready to use your skills to help solve problems? If so, we're looking for someone like you to join our team at APL.

 

We are in seeking an AI Solutions Engineer to provide expert knowledge in the realm of AI and ML systems, assisting researchers in pioneering research endeavors. This person will play a key role in ensuring the smooth operation, optimization and performance of our AI-driven products and services for advanced research.

 

As an AI Solutions Engineer …

• You will provide architectural expertise, direction, and assistance to developers, researchers and data scientists to support the AI model lifecycle
• Document operational procedures, guidelines, provide technical support and problem-solving assistance for AI platform users
• Collaborate with researchers and data scientists to design, develop and maintain scalable data pipelines for training and inference

Qualifications:

You’ll meet our minimum qualifications if you…

• Hold a Bachelor of Science degree or equivalent years of related professional work experience
• Have experience using container-based orchestration (e.g. Kubernetes) and run-time environments (e.g. Docker)
• Have experience in supporting AI and ML systems in production environment
• Have programming and scripting skills with Bash, Python or C++
• Familiarity with machine learning algorithms, frameworks and tools
• Stay abreast of emerging technologies and industry trends in AI and ML to continuously improve our offerings
• Demonstrate ability to investigate and resolve moderately complex problems using current job knowledge, research data and external resources
• Able to work effectively with leadership to prioritize competing tasks
• Demonstrate solid communication and listening skills within a collaborative team environment
• Ambitious to learn, effectively plan and organize work, seek and share knowledge on a continuous basis
• Assist in training and mentoring team members on AI-related technologies
• Are able to obtain Secret level security clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.

You’ll go above and beyond our minimum requirements if you…

• Experience securing Unix and cloud native applications
• Experience with AI/ML model deployment and management platform (e.g:- MLflow, Kubeflow)
• Experience with data engineering and streaming data analysis
• Familiarity with cloud computing platform (AWS, Azure or GCP)
• Knowledge of distributed computing and big data architectures (e.g. Hadoop, Spark)
• Knowledge of Agile and DevOps processes

Special Working Conditions:

• Occasional weekend and other after-hours work may be required to handle and/or complete critical work to meet APL's business needs.

 

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 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 www.jhuapl.edu/careers.

About Us:

APL is an Equal Opportunity/Affirmative Action employer. 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 promoting an innovative environment that embraces diversity, encourages creativity, and supports inclusion of new ideas. In doing so, we are 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 Accommodations@jhuapl.edu. Only by ensuring that everyone’s voice is heard are we empowered to be bold, do great things, and make the world a better place.

 

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 AnnuallyMaximum Rate:$150,000 Annually