Machine Learning Ops Engineer
Rome, New YorkOverview
General Atomics pioneers technologies with the potential to change the world. Behind a talented global team of engineers, GA delivers safe, sustainable, and economical solutions to meet growing global demands. Our Engineers have an opportunity to work on first of a kind product lines within an incredible, dynamic environment.
Engineering positions typically require a bachelor’s degree, master’s degree or PhD in engineering or a related technical discipline from an accredited institution and progressive engineering experience. Candidates from mechanical, electrical, and aerospace engineering backgrounds must know the fundamentals of engineering system developments, requirements, testing, and integration before getting to the final stages of customer interface and project management.
Schedule: Full-Time Salary
Job Level: Entry-Level (0-2 years)
Travel: 0 - 25
Success Profile
What makes a successful Machine Learning Ops Engineer at General Atomics? Check out the top traits we’re looking for and see if you have the right mix.
- Analytical
- Collaborative
- Inventive
- Problem Solver
- Team Player
- Creative
Job Summary
From concept-to-deployment, General Atomics North Point Defense, Inc. (GA-NPD), a division of General Atomics Integrated Intelligence, Inc. (GA-Intelligence), provides AI/ML-based autonomous signal processing and data dissemination solutions providing real-time actionable intelligence supporting tactical and national mission priorities. At GA-NPD, we take a tailored approach meeting our customers’ unique intelligence needs.
We are seeking an MLOps engineer who will streamline the end-to-end machine learning lifecycle, from research, development and experimentation to deployment and monitoring in production environments. This role demands applying software engineering best practices, such as continuous integration (CI) and continuous delivery (CD), to machine learning systems, ensuring ML models are not just developed but are also scalable, reliable, and continuously perform well in real-world applications.
Our team of experts work closely with the end-user in the development and implementation of a defense solution meeting platform and/or site-specific requirements. We pride ourselves as a trusted Defense Industry partner and deliver top-notch services far exceeding typical industry standards.
DUTIES AND RESPONSIBILITIES:
- Package ML models in containers, i.e. Docker, and deploy to production environments.
- Design and implement ML pipelines for data ingestion, training, evaluation, and deployment.
- Setup and maintain model monitoring and logging of deployed models to track performance metrics like accuracy, latency, and resource utilization.
- Collaborate with a diverse team including data scientists to transition models from research to production, software engineers to integrate ML models into broader application architectures, and system engineers to maximize hardware resources (cpu, fpga, gpu) to optimize performance.
Job Qualifications:
- Typically requires a bachelors degree in computer science, engineering, mathematics, or a related technical discipline from an accredited institution. May substitute equivalent machine learning engineer experience in lieu of education.
- Strong proficiency in Python. Experience with other languages like C++ is also valuable.
- Understanding of machine learning principles and frameworks like PyTorch (preferred), TensorFlow, etc.
- Practical experience with Docker for deployment and packaging applications.
- Experience with optimizers such as TensorRT, onnx, and openVino.
- Proficient with Linux command line environment.
- Ability to obtain and maintain DoD Security Clearance is required.
Salary:$81,000 - $141,533
Benefits
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Healthcare
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Pension, 401(k)/Retirement Plans
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Competitive Pay
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Multiple product lines means a variety of work
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Paid Time Off
“The company is growing, has a very good reputation and had open positions in my area of expertise (aircraft design/design methodology development).”– Peter, Senior Staff Engineer
“We don't ascribe to quotas; we do ascribe to securing the BEST talent to enrich our culture toward healthy diversification and active/viable community service. We are STEM advocates.”– Debra, CSSBB: Staff Engineer
“Every day is different, with different problems to solve and many programs to support. I am a problem solver and have always been motivated by the tough questions.”– Scott, Laser Scientist
“I work in the Components Engineering and Obsolescence Management Dept. Our efforts are saving General Atomics several millions of dollars by proactively leading and informing the company of all these decisions which significantly impact production, sustainment and new designs.”– John, Staff Engineer
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