ML Engineer
Omaha, NE · On-site
... ML inference systems that handle high-volume, low-latency predictions in production environments Create comprehensive monitoring and alerting systems for model performance, data drift, and system ...
ML Engineer
Omaha, NE · On-site
... ML inference systems that handle high-volume, low-latency predictions in production environments Create comprehensive monitoring and alerting systems for model performance, data drift, and system ...
Senior Machine Learning Engineer
Bellevue, NE · On-site
$99K - $135K/yr
Strong understanding of ML model evaluation, A/B testing, and statistical/causal inference; depth in one or more of recommendations & ranking, identity resolution, embeddings/retrieval, forecasting ...
Senior Machine Learning Engineer
Bellevue, NE · On-site
$99K - $135K/yr
Strong understanding of ML model evaluation, A/B testing, and statistical/causal inference; depth in one or more of recommendations & ranking, identity resolution, embeddings/retrieval, forecasting ...
Senior Machine Learning Engineer
Bellevue, NE · On-site
$99K - $135K/yr
Strong understanding of ML model evaluation, A/B testing, and statistical/causal inference; depth in one or more of recommendations & ranking, identity resolution, embeddings/retrieval, forecasting ...
Senior Machine Learning Engineer
Bellevue, NE · On-site
$99K - $135K/yr
Strong understanding of ML model evaluation, A/B testing, and statistical/causal inference; depth in one or more of recommendations & ranking, identity resolution, embeddings/retrieval, forecasting ...
Data and Analytics - AI Engineer II
Omaha, NE · On-site +1
$107K - $150K/yr
... ML solutions for various business units * Design and integrate Agentic processes into enterprise systems and workflows * Maintain and optimize data pipelines for training and inference * Monitor ...
Data and Analytics - AI Engineer II
Omaha, NE · On-site +1
$107K - $150K/yr
... ML solutions for various business units * Design and integrate Agentic processes into enterprise systems and workflows * Maintain and optimize data pipelines for training and inference * Monitor ...
Data Scientist
Omaha, NE · On-site
As a Data Scientist at Agile Defense, you will be joining a team of professionals that build AI/ML ... inference, and statistical modeling techniques Strong programming skills in Python or R with ...
Data Scientist
Omaha, NE · On-site
As a Data Scientist at Agile Defense, you will be joining a team of professionals that build AI/ML ... inference, and statistical modeling techniques Strong programming skills in Python or R with ...
As a Data Scientist at Agile Defense, you will be joining a team of professionals that build AI/ML ... inference, and statistical modeling techniques · Strong programming skills in Python or R with ...
As a Data Scientist at Agile Defense, you will be joining a team of professionals that build AI/ML ... inference, and statistical modeling techniques · Strong programming skills in Python or R with ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
The Opportunity: We're looking for a Principal AI/ML Engineer to lead the architecture and ... Building scalable inference and retrieval services capable of serving physicians around the world.
The Opportunity: We're looking for a Principal AI/ML Engineer to lead the architecture and ... Building scalable inference and retrieval services capable of serving physicians around the world.
Ml Inference information
What is ML inference?
ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.
What is the difference between Ml Inference vs Data Scientist?
| Aspect | ML Inference | Data Scientist |
|---|---|---|
| Required Credentials | Knowledge of machine learning models, programming skills | Degree in data science, statistics, or related fields |
| Work Environment | Deploying models in production, real-time data processing | Data analysis, model development, research |
| Industry Usage | AI product deployment, software companies | Research institutions, tech firms, consulting |
ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.
What are some common challenges faced by ML inference engineers when deploying models to production?
ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.
What are the key skills and qualifications needed to thrive in ML inference?
To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.
Is ML inference a high paying job?
ML inference roles are generally well-paying, especially for those with skills in machine learning frameworks, programming, and cloud platforms. Salaries vary based on experience, location, and industry, but they tend to be higher than average for tech-related positions.
What are popular job titles related to Ml Inference jobs in Nebraska? For Ml Inference jobs in Nebraska, the most frequently searched job titles are:
What job categories do people searching Ml Inference jobs in Nebraska look for? The top searched job categories for Ml Inference jobs in Nebraska are:
What cities in Nebraska are hiring for Ml Inference jobs? Cities in Nebraska with the most Ml Inference job openings:
Job description
About Agile Defense
At Agile Defense we know that action defines the outcome and new challenges require new solutions. That's why we always look to the future and embrace change with an unmovable spirit and the courage to build for what comes next.
Our vision is to bring adaptive innovation to support our nation's most important missions through the seamless integration of advanced technologies, elite minds, and unparalleled agility-leveraging a foundation of speed, flexibility, and ingenuity to strengthen and protect our nation's vital interests.
Requisition #: 1418
Job Title: ML Engineer
Location: Omaha, NE
Clearance Level: Active DoD Top Secret
Overview:
At Agile Defense we know that action defines the outcome and new challenges require new solutions. That's why we always look to the future and embrace change with an unmovable spirit and the courage to build for what comes next.
Our vision is to bring adaptive innovation to support our nation's most important missions through the seamless integration of advanced technologies, elite minds, and unparalleled agility-leveraging a foundation of speed, flexibility, and ingenuity to strengthen and protect our nation's vital interests. We are currently looking for an ML Engineer to support our contract with the DRAID CDAO ADA IR Program.
As an ML Engineer at Agile Defense, you will be joining a team of professionals that secure, scalable data architectures and AI/ML pipelines. This role will support data science and engineering activities, partnering with product teams, data engineers, mission stakeholders, and technologists to unlock the value of structured and unstructured data in support of national defense priorities. You will implement data engineering activities and develop and deploy pipelines and platforms that organize and make complicated data meaningful.
Responsibilities/Duties:
Build Scalable Data & ML Infrastructure
Design and implement medallion architecture (Bronze/Silver/Gold) using Databricks for reliable data processing and ML model training
Develop automated data pipelines that process structured and unstructured data from multiple sources into analytics-ready formats
Create robust ETL/ELT workflows using Apache Spark and modern data engineering practices for both batch and streaming data
Build and maintain data quality monitoring and validation systems across the entire data and ML lifecycle
Drive ML Platform Excellence
Implement MLOps best practices including automated model training, validation, deployment, and monitoring using MLflow and Databricks workflows
Design scalable ML inference systems that handle high-volume, low-latency predictions in production environments
Create comprehensive monitoring and alerting systems for model performance, data drift, and system health
Build self-service ML capabilities that enable data scientists to deploy and monitor their own models efficiently
Enable Advanced Analytics & Business Intelligence
Design and maintain data models that support both machine learning workloads and business intelligence requirements
Create integration points between ML systems and business intelligence platforms (Tableau, PowerBI, Qlik Sense)
Implement data governance standards and metadata management systems that ensure data quality and compliance
Collaborate with analysts and data scientists to optimize data architecture for both predictive modeling and reporting needs
Ensure Data Quality & Governance
Implement comprehensive data governance frameworks including data lineage tracking, quality monitoring, and compliance controls
Design and maintain data catalogs and metadata management systems that enable efficient data discovery across the organization
Establish data quality standards and automated testing frameworks for both analytical and ML workloads
Work with stakeholders to define data definitions, business logic, and governance policies
Integrate with Enterprise Systems
Build integrations with MAVEN Smart Systems (Palantir Foundry) environments to support operational and predictive analytics
Connect Databricks-based systems with enterprise data warehouses, streaming platforms, and business applications
Implement security and compliance controls that meet enterprise requirements while enabling self-service capabilities
Collaborate with platform engineers to integrate ML systems with broader application architecture and infrastructure
Required Skills - What You'll Bring:
5+ years of technical experience, including 3+ years building production data pipelines and ML infrastructure using distributed computing platforms like Databricks.
Strong data engineering skills in Python, PySpark, and Spark SQL with experience implementing medallion architecture and modern data platform patterns
Production ML systems experience including model deployment, monitoring, and MLOps practices in cloud environments
Data architecture expertise with experience designing scalable data processing systems and implementing data governance frameworks
Experience integrating with platforms such as Qlik, Tableau, PowerBI, MAVEN Smart System (Palantir), or similar.
Preferred Skills - What Would Set You Apart:
Deep expertise in distributed computing, performance optimization, and large-scale data processing using Databricks and Apache Spark
Advanced MLOps knowledge including automated retraining, model versioning, model testing frameworks, and production ML monitoring
Experience conducting regression analysis, and building predictive models for business applications with measurable impact
Advanced statistical knowledge including experimental design, hypothesis testing, causal inference, and statistical modeling techniques
Experience designing and building enterprise-level dashboards, reports, and self-service analytics platforms
Analytics platform knowledge including experience with Advana / MAVEN Smart Systems (Palantir Foundry) or similar enterprise analytics environments
Our Core Values
Employees of Agile Defense are our number one priority, and the importance we place on our culture here is fundamental. Our culture is alive and evolving, but it always stays true to its roots. Here, you are valued as a family member, and we believe that we can accomplish great things together. Agile Defense has been highly successful in the past few years due to our employees and the culture we create together.
What makes us Agile? We call it the 6Hs, the values that define our culture and guide everything we do. Together, these values infuse vibrancy, integrity, and a tireless work ethic into advancing the most important national security and critical civilian missions. It's how we show up every day. It's who we are.
- Happy - Be Infectious. Happiness multiplies and creates a positive and connected environment where motivation and satisfaction have an outsized effect on everything we do.
- Helpful - Be Supportive. Being helpful is the foundation of teamwork, resulting in a supportive atmosphere where collaboration flourishes, and collective success is celebrated.
- Honest - Be Trustworthy. Honesty serves as our compass, ensuring transparent communication and ethical conduct, essential to who we are and the complex domains we support.
- Humble - Be Grounded. Success is not achieved alone, humility ensures a culture of mutual respect, encouraging open communication, and a willingness to learn from one another and take on any task.
- Hungry - Be Eager. Our hunger for excellence drives an insatiable appetite for innovation and continuous improvement, propelling us forward in the face of new and unprecedented challenges.
- Hustle - Be Driven. Hustle is reflected in our relentless work ethic, where we are each committed to going above and beyond to advance the mission and achieve success.
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
apply for this job
About Agile Defense
Sourced by ZipRecruiter
Industry
It services
Company size
201 - 500 Employees
Headquarters location
Reston, VA, US
Year founded
1998