Senior Machine Learning Operations Engineer
- Location
- New York, NY · On-site
- Job type
- Full-time
- Level
- Senior
- Experience
- 5+ years
- Education
- Bachelor's degree
- Listed
- 30 days ago
Skills & highlights for this role
- Python
- TensorFlow
- PyTorch
- Docker
- Kubernetes
Also useful
- TensorRT
- C++
- AWS
What You'll Do
- Design, develop, and implement end-to-end machine learning pipelines, from data ingestion and preprocessing to model training, evaluation, and deployment.
- Collaborate with the general software engineering team to integrate ML models into existing software systems and ensure scalability and maintainability.
- Work in conjunction with computer vision specialists to apply and optimize ML techniques for image and video analysis, object detection, tracking, and recognition in defense contexts.
- Research and evaluate new machine learning algorithms, tools, and technologies to enhance our capabilities and solve challenging problems.
- Perform rigorous model testing, validation, and performance tuning to ensure robustness and accuracy in real-world scenarios.
- Contribute to the development of best practices for ML engineering, including MLOps, version control, and reproducible research.
- Mentor junior engineers and contribute to a culture of continuous learning and knowledge sharing.
- Communicate technical concepts effectively to both technical and non-technical stakeholders.
What You'll Need
- Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of experience in machine learning engineering, with a proven track record of deploying ML models in production environments.
- Technical Skills:
- Strong proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Solid understanding of core machine learning concepts, including supervised, unsupervised, and reinforcement learning.
- Experience with various machine learning model architectures and their application (e.g., CNNs, RNNs, Transformers, decision trees, support vector machines).
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
- Experience with MLOps tools and practices.
- Experience deploying a variety of edge systems.
- Experience with TensorRT and other similar technologies.
- Deep knowledge of C++ and Python.
- Domain Knowledge:
- Experience or strong interest in defense, aerospace, or related industries is highly desirable.
- Understanding of the unique challenges and considerations for deploying ML in defense applications (e.g., adversarial robustness, real-time constraints, data security).
- Collaboration & Communication:
- Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
- Ability to translate complex technical concepts into clear and concise language.
- Problem-Solving:
- Strong analytical and problem-solving skills, with a proactive and innovative approach.
- Ability to work independently and manage multiple priorities in a fast-paced environment.
Bonus Points
- Experience with specific computer vision tasks such as object detection, segmentation, or tracking.
- Familiarity with real-time ML systems and embedded systems.
- Contributions to open-source projects or publications in relevant fields.
What We Offer
- Competitive salary, equity, and benefits package.
- Opportunity to work on cutting-edge technology with a significant impact on national security.
- A collaborative work environment that values innovation.
- Professional development opportunities and career growth.
About US
ZeroMark builds AI-driven counter-drone systems that actually work in combat. No PowerPoints. No hype. Just field-proven technology that saves lives.
We've doubled year-over-year for two straight years, winning contracts that prove what we've always known: real innovation happens in the dirt, not in conference rooms. Our systems transform standard weapons into AI-powered platforms that detect, track, and neutralize drone threats-because a $200 drone shouldn't require a million-dollar countermeasure.
Here's what makes us different: ZeroMark operators don't build from behind screens. You'll validate tech from Blackhawk helicopters, train alongside Tier-1 units (who happen to be our coworkers), and test at legendary ranges from White Sands to the cliffs of Hawaii. When we say field-tested, we mean you'll shoot it, fly with it, and push it to failure. We don't tweet about changing the world-we're too busy actually doing it.
If you want to make an actual impact-and have some unforgettable Tuesday afternoons along the way-let's talk. We're all about delivering practical, field-tested tech, not just theories.
From Zeromark's careers page, first listed on Rolev.ai on October 10, 2026. Rolev.ai is not the employer.
How Rolev.ai helps with this application
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Common questions
Where is the Senior Machine Learning Operations Engineer job at Zeromark located?
This Senior Machine Learning Operations Engineer position at Zeromark is located in New York, NY (On-site). Always check Zeromark's application page for specific state eligibility or relocation policies.
What qualifications are required for Senior Machine Learning Operations Engineer at Zeromark?
For the Senior Machine Learning Operations Engineer role, Zeromark highlights 5+ years of relevant experience; a bachelor's degree; experience with Python, TensorFlow, PyTorch, Docker, Kubernetes. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Senior Machine Learning Operations Engineer position at Zeromark?
This listing links directly to Zeromark's Ashby application page. You can apply directly on Zeromark's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Ashby application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.