Our company is a global leader in space-based intelligence solutions, trusted for over two decades by the world's leading defense and intelligence agencies.
We specialize in delivering custom-made solutions that meet the strategic intelligence requirements and challenges of our clients.
We are looking for a highly motivated and experienced ML Engineer to join our dynamic team.
In this role, you will be designing, implementing, and deploying advanced Machine Learning pipelines to enhance the intelligence capabilities of our solutions.
You will work closely with data scientists, software developers, and DevOps teams to ensure seamless integration and deployment of these technologies in production environments.
This role is an opportunity to be at the forefront of technological innovation in space-based intelligence.
You will work with a team of experts dedicated to maintaining our standing as a leader in the industry and will have the chance to contribute to projects of national and international significance.
Responsibilities:
* Design and develop sophisticated Machine Learning (ML) pipelines end-to-end, tailored for scalability, usability, and high performance.
* Collaborate with software developers and data scientists to integrate Machine Learning technologies into robust production systems.
* Continuously monitor and evaluate the performance of deployed models, optimizing them through regular testing, experimentation, and updates.
* Keep track of the latest advancements in Machine Learning and related technologies, integrating cutting-edge solutions to enhance product offerings.
* Manage data from diverse sources, develop features from raw data, and build comprehensive end-to-end ML pipelines.
Requirements: * Minimum of 5 years of hands-on experience in Python programming for Machine Learning applications.
* Proficient in crafting clean, modular, and reusable code with a strong emphasis on production-quality implementations.
* Strong foundation in using major Machine Learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
* Proven expertise in developing, deploying, and managing Machine Learning models and algorithms.
* Advanced skills in system architecture and design, capable of analyzing requirements, defining system components, and engineering scalable software solutions.
* Experience with AWS cloud services, focusing on Storage and messaging; familiarity with hybrid cloud/on-prem environments is a plus.
* Knowledge of Docker and Kubernetes, for efficient deployment of Machine Learning solutions.
* Excellent teamwork, communication, and problem-solving skills, essential for cross-functional collaboration and innovation.
Advantages:
* Background in GIS and experience processing large-scale satellite or drone imagery.
* Vast experience designing and implementing end-to-end ML pipelines and tools, including components such as experiment tracking, data version control, and scalable training pipelines.
* Deep understanding of Relational and non-Relational Databases.
* Experience with distributed computing frameworks such as DASK or Ray.
This position is open to all candidates.