Machine Learning Engineer
Gulfport, MS · On-site
Optimize and deploy models for real-time inference on size, weight, and power constrained edge ... Integrate ML components into production software and autonomy pipelines, ensuring reliable ...
Machine Learning Engineer
Gulfport, MS · On-site
Optimize and deploy models for real-time inference on size, weight, and power constrained edge ... Integrate ML components into production software and autonomy pipelines, ensuring reliable ...
AI Engineer
Hattiesburg, MS · On-site
... inference infrastructure and pipelines. * Implement MLOps pipelines for continuous integration, deployment, and lifecycle management using Azure ML and GitHub Actions. * Ensure compliant change ...
AI Engineer
Hattiesburg, MS · On-site
... inference infrastructure and pipelines. * Implement MLOps pipelines for continuous integration, deployment, and lifecycle management using Azure ML and GitHub Actions. * Ensure compliant change ...
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 ...
... of ML models, or software architecture - when a program needs concentrated effort, and they can ... Edge-deployed sensor processing and on-platform inference under power, bandwidth, and comms ...
... of ML models, or software architecture - when a program needs concentrated effort, and they can ... Edge-deployed sensor processing and on-platform inference under power, bandwidth, and comms ...
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 Mississippi? For Ml Inference jobs in Mississippi, the most frequently searched job titles are:
What job categories do people searching Ml Inference jobs in Mississippi look for? The top searched job categories for Ml Inference jobs in Mississippi are:
What cities in Mississippi are hiring for Ml Inference jobs? Cities in Mississippi with the most Ml Inference job openings:
Full-time
Medical, Dental, Vision, Retirement, PTO
Re-posted 5 days ago
Integer Holdings rating
7.3
Based on 41 frontline employees who took The Breakroom Quiz
321st of 538 rated manufacturers
Job description
About the role
Integer Technologies is seeking a Machine Learning Engineer to develop, optimize, and deploy AI/ML methods that power perception and autonomy for maritime platforms. This role sits at the intersection of data science and software engineering: you will design models that turn raw maritime sensor data into reliable detection, classification, and situational awareness, and you will be responsible for integrating those models into production software that runs on the edge. Candidates must be U.S. citizens, eligible for a DoD security clearance, and capable of working across multidisciplinary teams to deliver scalable, maintainable, and mission-ready systems. Experience in maritime autonomy, sensor fusion, and distributed systems is highly desirable
What you'll do
Qualifications
OR
Additional Desired Qualifications
About Integer Technologies
Integer Technologies is an applied research and product development company founded by scientists and engineers with a passion for protecting freedom with innovation. We perform R&D on next-generation systems and technologies for the Department of Defense and other U.S. Government agencies. We are hardware and software developers with experience transforming research into fieldable technology. Our core portfolio of research includes projects in power & energy systems, unmanned systems (with an emphasis on maritime systems), digital engineering, cyber security, and advanced manufacturing. Our mission is to create a safer world by translating scientific discoveries into reliable products that address urgent national security needs... at the speed of relevance.
Company Benefits
Company Perks
Integer Technologies is seeking a Machine Learning Engineer to develop, optimize, and deploy AI/ML methods that power perception and autonomy for maritime platforms. This role sits at the intersection of data science and software engineering: you will design models that turn raw maritime sensor data into reliable detection, classification, and situational awareness, and you will be responsible for integrating those models into production software that runs on the edge. Candidates must be U.S. citizens, eligible for a DoD security clearance, and capable of working across multidisciplinary teams to deliver scalable, maintainable, and mission-ready systems. Experience in maritime autonomy, sensor fusion, and distributed systems is highly desirable
What you'll do
- Model Development: Design, train, and evaluate machine learning and deep learning models for detection, classification, segmentation, tracking, and signal analysis using maritime sensor data, with particular emphasis on sonar and other maritime sensors.
- Sensor Data & Fusion: Develop methods to process, fuse, and exploit heterogeneous sensor streams (sonar, magnetics, IMU, etc.) to produce robust perception in challenging maritime conditions.
- Edge Deployment: Optimize and deploy models for real-time inference on size, weight, and power constrained edge compute, applying techniques such as quantization, pruning, distillation, and hardware acceleration (e.g., GPU/CUDA, TensorRT, embedded accelerators).
- Software Integration: Integrate ML components into production software and autonomy pipelines, ensuring reliable interfaces with sensors, middleware, and downstream systems; write well-tested, maintainable code under version control.
- Data Pipelines & Tooling: Build pipelines and tooling for data ingestion, labeling, augmentation, and the creation of training and validation datasets that reflect real operational environments.
- Research & Innovation: Stay current with advances in AI/ML and signal processing, and identify opportunities to extend perception and autonomy capabilities based on evolving mission requirements
- Collaboration & Mentorship: Work across multidisciplinary teams and external partners, and contribute to a culture of technical excellence, knowledge sharing, and development best practices
Qualifications
- Must be a U.S. Citizen with the ability to obtain and maintain a U.S. DoD Secret Clearance.
- Bachelor's degree in relevant fields (e.g., data science, computer science, computer engineering, electrical engineering, mechanical engineering, or other related field) and 7+ years of experience relevant to primary responsibilities outlined above.
OR
- Master's degree in relevant field (e.g., data science, computer science, computer engineering, electrical engineering, mechanical engineering, or other related field) and 5+ years of experience relevant to primary responsibilities outlined above.
- Strong proficiency in modern programming languages (e.g., C++, Python) and common ML frameworks (e.g., PyTorch or TensorFlow), with solid software engineering fundamentals and experience using Git
- Demonstrated experience taking ML models from prototype to integrated software
- Solid foundation in the mathematics underpinning ML, including linear algebra, probability and statistics, and signal processing.
- Experience working with real sensor data and an understanding of the challenges of noisy, real-world signals.
- Excellent written and oral communication skills, and the ability to collaborate effectively across disciplines.
Additional Desired Qualifications
- Ph.D. in relevant field (e.g., data science, computer science, computer engineering, electrical engineering, mechanical engineering, or other related field)
- Experience developing robotic or autonomous systems, using data from various perception sensor types (sonar, magnetic, cameras, lidar, etc.) to enhance a robotic platform's perception of its surrounding environmental and potential navigational hazards
- Experience with unmanned and autonomous systems research involving maritime autonomous systems such as uncrewed surface vessels and uncrewed underwater vessels.
- Experience with edge processing
- Understanding of the Navy and Department of Defense's mission, problem set, and strategy for the integration of autonomous systems.
About Integer Technologies
Integer Technologies is an applied research and product development company founded by scientists and engineers with a passion for protecting freedom with innovation. We perform R&D on next-generation systems and technologies for the Department of Defense and other U.S. Government agencies. We are hardware and software developers with experience transforming research into fieldable technology. Our core portfolio of research includes projects in power & energy systems, unmanned systems (with an emphasis on maritime systems), digital engineering, cyber security, and advanced manufacturing. Our mission is to create a safer world by translating scientific discoveries into reliable products that address urgent national security needs... at the speed of relevance.
Company Benefits
- Integer fully covers medical, prescription, vision, and dental insurance costs for the employee and dependents. Meaning, Integer standard plan pays 100% of health insurance premiums for your entire family from a well-known national insurer, saving its employees thousands of dollars annually.
- Relocation assistance available.
- Base salaries which exceed local & national industry averages.
- Year-end performance-based bonuses.
- 401(k) with company matching that vest immediately; no funny business.
- Paid Vacation
- Paid Sick Leave
- Paid Holidays
Company Perks
- Startup culture with the stability of a large company. Integer's business plan has years of time phased contracted work, alleviating the would-be risk from a traditional small company.
- Direct access to company leadership, prioritization of people over process, and a stellar team with a shared desire for personal and professional growth.
- Friendly atmosphere where people enjoy not only their work and what they're creating but enjoy helping each other as well.
- Waterfront office view!
What Integer Holdings employees say
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Benefits
Hours and flexibility
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