Senior Machine Learning Operations Engineer

ZeroMark, Inc.; New York (NY); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Competitive salary

Equity

Professional development opportunities

Collaborative culture

Career growth opportunities

Job summary

A technology company in New York is seeking a Senior Machine Learning Generalist to design and implement machine learning models for defense applications. The ideal candidate will have over 5 years of experience in machine learning engineering, strong Python skills, and the ability to collaborate with cross-functional teams. This role offers competitive salary, equity, and the opportunity to work on cutting-edge technology impacting national security.

Qualifications

• 5+ years of experience in machine learning engineering.
• Strong proficiency in Python and relevant ML libraries.
• Knowledge of deploying ML models in production environments.
• Experience with ML model architectures (CNNs, RNNs, Transformers) and edge deployment.
• Familiarity with cloud platforms and containerization (Docker, Kubernetes).
• Understanding of MLOps practices and real-time defense application considerations.
• Excellent collaboration, communication, and problem-solving skills.

Responsibilities

• Design and implement machine learning pipelines.
• Collaborate with engineering teams to integrate ML models.
• Research new algorithms to enhance capabilities.
• Research and evaluate new ML algorithms and tools to enhance capabilities.
• Perform model testing, validation, and performance tuning for real-world scenarios.
• Contribute to ML engineering best practices, version control, and reproducible research.
• Mentor junior engineers and promote knowledge sharing.
• Communicate complex technical concepts to both technical and non-technical stakeholders.

Skills

Machine Learning Engineering

Python programming

Communication skills

CNNs / RNNs / Transformers

Edge deployment

MLOps

Cloud platforms (AWS, Azure, GCP)

C++ and Python

Communication & collaboration

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

TensorFlow

PyTorch

Docker

Kubernetes

Job description

The Role

We are seeking a highly skilled and experienced Senior Machine Learning Generalist to join our talented team. This individual will play a crucial role in designing, developing, and deploying machine learning models across various defense applications. You will work closely with both our general software engineering team and our computer vision engineering team, bridging the gap between foundational software development and advanced computer vision applications. This role requires a strong understanding of diverse ML techniques, excellent problem‑solving abilities, and the capacity to adapt to evolving project needs.

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.

Preferred Qualifications

• 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.

Benefits

• 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.