Outside Analytics has recently become a proud subsidiary of SMX, marking an exciting collaboration that enhances our collective capabilities to deliver cutting-edge digital transformation solutions.
Are you interested in the next generation of Space Force Remote Sensing capabilities? At Outside Analytics we’re on the ground floor of helping across the future remote sensing ecosystem across all orbital regimes (LEO, MEO, HEO, and GEO)! We build, integrate, and operationally support our customer’s emerging space-ground systems to include real-time data processing frameworks, sensor data processing, and data visualization. We are teamed with the most passionate companies in industry, dedicated to bringing best-of-breed capabilities to address our customers most pressing needs.
We are seeking an experienced Machine Learning Operations (MLOps) Engineer to join and help shape our new MLOps team. This role focuses on deploying and optimizing machine learning models for always-on, high-availability systems in real-world, real-time unclassified and classified environments. As part of a new and growing team, you will have the unique opportunity to evangelize MLOps practices, contribute to the development of an on-premises development platform, and drive innovation in mission-critical applications.

REQUIRED SKILLS & EXPERIENCE

• Secret clearance
• 4+ years, including deploying and/or maintaining at least one ML model or pipeline in a production environment.
• Proficiency in writing clean, maintainable code for automation and basic scripting tasks
• Basic familiarity with MLflow, Kubeflow, or similar platforms for managing ML experiments and pipelines
• Strong problem-solving and analytical skills
• Excellent communication and collaboration capabilities
• Ability to thrive in a dynamic, fast-paced environment
• Good written and verbal communication skills
• Detail oriented

DESIRED SKILLS & EXPERIENCE

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related technical field
• Relevant certifications (e.g., Certified Kubernetes Administrator, Certified Kubernetes Application Developer, Terraform Associate) are a plus
• Familiarity with C++ and/or Rust.
• Experience with workflow orchestration tools such as Airflow or Prefect
• Experience with distributed data processing frameworks such as PySpark
• Familiarity with SQL and modern database technologies (e.g., MinIO, Yugabyte)
• Experience with DVC, Ansible, Kustomize, Helm, Prometheus, and Grafana
• Understanding of secure software development practices and/or experience working in classified environments
  Application Deadline: May 19, 2025
  

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At SMX®, we are a team of technical and domain experts dedicated to enabling your mission. From priority national security initiatives for the DoD to highly assured and compliant solutions for healthcare, we understand that digital transformation is key to your future success.
We share your vision for the future and strive to accelerate your impact on the world. We bring both cutting edge technology and an expansive view of what’s possible to every engagement. Our delivery model and unique approaches harness our deep technical and domain knowledge, providing forward-looking insights and practical solutions to power secure mission acceleration.
All qualified candidates will receive consideration for employment without regard to disability status, protected veteran status, race, color, age, religion, national origin, citizenship, marital status, sex, sexual orientation, gender identity or expression, pregnancy or genetic information.
Selected applicant may be subject to a background investigation and/or education verification

• Deploy and maintain high-performing ML models (e.g., ensembles of LSTMs and Random Forests) in real-time environments to continually improve mission processing (event detection and characterization) results
• Monitor deployed models for drift or performance degradation and implement automated retraining pipelines.
• Develop modular and flexible ML pipelines that ensure uptime and reliability
• Set up robust monitoring, logging, and alerting systems using Prometheus, Grafana, and Loki or similar systems
• Optimize performance metrics like inference latency and system throughput while ensuring fault tolerance
• Work with cross-functional teams, including Data Engineering, Machine Learning, and DevOps, to integrate and enhance ML systems
• Define touchpoints and handoffs with DevOps and Data Engineering to ensure seamless integration of ML workflows with existing infrastructure and data pipelines
• Mentor junior team members and contribute to building a collaborative and innovative team culture
• Other duties as assigned