ML Ops Engineer - Clearance Required

United States Digital Space LLC; United States; Hybrid; USD 110,000 - 185,000; Full time

Job summary

United States Digital Space LLC seeks a Machine Learning Operations Engineer to support Army AI initiatives, integrating ML workflows into scalable, mission-critical applications.

The role includes deploying models to web apps, building robust ML CI/CD pipelines, and collaborating with Army stakeholders to design generative AI tools that empower decision-making and operational effectiveness.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Software Engineering, or related field.
• 3+ years of experience in machine learning engineering, with emphasis on MLOps, model development, and deployment.
• Experience with data manipulation/pipelining (Pandas, PySpark).
• Hands-on ML model development using Scikit-Learn, MLlib, TensorFlow, PyTorch, etc.
• Production deployment of AI/ML models in web-based applications.
• Proficiency with Python and Python-based web frameworks (Flask, Django, FastAPI).
• Experience with Docker and Kubernetes.
• Familiarity with Agile/Scrum, CI/CD, and Git.
• Ability to work in ambiguous environments; Active Secret Clearance.

Responsibilities

• Build, train, validate, and evaluate ML models with Scikit-Learn, TensorFlow, or similar tools.
• Develop generative AI applications and ensure real-world applicability of models.
• Deploy ML models to web-based applications and integrate into operational environments.
• Operationalize generative AI systems with scalable pipelines across environments.
• Design data manipulation pipelines using Pandas and PySpark for training and analysis.
• Support ML CI/CD pipelines and DevSecOps collaboration for deployments.
• Collaborate with Army stakeholders to identify ML integration opportunities and translate needs into requirements.
• Mentor junior team members and lead architectural discussions to strengthen ML capabilities.
• Engage with government customers and contribute to strategic documentation for AI/ML projects.

Skills

Python

ML/DL

CI/CD

Git

Cloud

Security Clearance

Education

Bachelor's degree in CS/Data Science/SE

Tools

Docker

Kubernetes

Pandas

PySpark

Scikit-Learn

TensorFlow/PyTorch

Job description

Overview:

the company is seeking a Machine Learning Operations Engineer (ML Ops Engineer) to support the development of cutting-edge AI/ML solutions in collaboration with the Army’s AI2C organization. This role emphasizes integrating machine learning workflows into scalable, efficient applications while addressing operational needs for the United States Army. The ML Ops Engineer will work at the intersection of advanced AI/ML development, machine learning system deployment, and mission-critical applications, ensuring end-to-end lifecycle management of AI capabilities.

This position provides an exciting opportunity to collaborate directly with the Army to design cutting-edge generative AI tools and machine learning systems to empower their operations and decision-making. Candidates should thrive in a fast-paced, collaborative environment and demonstrate technical creativity, continuous learning, and problem-solving expertise.

the company is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, the company brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.

Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, the company serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, the company is committed to delivering impactful results that strengthen missions and drive lasting value.

Responsibilities:

• Build, train, validate, and evaluate machine learning models using technologies such as Scikit-Learn, TensorFlow, or similar tools.
• Research, develop, and implement generative AI applications, ensuring that models address complex real-world challenges effectively.
• Deploy machine learning models to web-based applications and integrate them into operational environments.

• Operationalize generative AI systems by developing robust, scalable pipelines for deployment across multiple environments.
• Design and implement advanced data manipulation and pipelining workflows using tools such as Pandas and PySpark to support model training and analysis.
• Support CI/CD pipelines tailored for ML model development and deployment.
• Work alongside other engineering and DevSecOps teams to support scalable cloud-based deployments.
• Collaborate directly with Army stakeholders to identify strategic opportunities for ML integration, addressing challenges and providing innovative technical solutions.
• Assist product leads in translating operational needs and feedback into actionable technical requirements and strategies.
• Mentor junior team members, guiding their ML and MLOps skill development while contributing to process improvements.
• Lead discussions on architecture, system design, technology adoption, and team development to strengthen the company’s ML capabilities.
• Build and maintain strong relationships with government customers and stakeholders through hybrid on-site engagement.
• Contribute to technical narratives for proposals, white papers, and strategic documentation for expanding AI/ML and ML Ops projects within Army domains.

Percentage of Travel Required: 10%

Qualifications:

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Data Science, Software Engineering, or a related field.
• 3+ years of experience in machine learning engineering, with particular emphasis on MLOps, model development, and deployment.
• Demonstrated expertise in data manipulation & pipelining technologies, such as Pandas or PySpark.
• Hands-on experience developing machine learning models using tools such as Scikit-Learn, MLlib, TensorFlow, PyTorch, etc.
• Practical experience in deploying AI/ML models in production web-based applications.
• Advanced proficiency with Python and Python-based web frameworks (e.g., Flask, Django, FastAPI, etc.).
• Strong understanding and hands-on experience with containerization technologies, such as Docker and Kubernetes.
• Familiarity with Agile or Scrum methodologies, CI/CD practices, and version control systems (e.g., Git).
• Comfort operating in ambiguous and dynamic environments requiring proactive problem-solving.
• Active Secret Clearance required

Additional Preferred Qualifications:

• 7+ years of directly related experience.
• Proven track record using MLOps workflows (e.g., MLFlow, Kubeflow), including monitoring, orchestrating, and scaling production models.
• Hands-on deployment experience across multiple environments and platforms
• Experience integrating machine learning and analytical tools
• Background working in strategic planning or consultant environments supporting government or DoD clients
• Proven track record of expanding technical scope or footprint with government customers
• Knowledge of the Army software development process and its technologies.

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Target salary range: $110,075 - $185,138

Disclaimer:The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.

Job Locations: US-Remote US-PA-Pittsburgh