Machine Learning Engineer (SC)
Posted 2 weeks ago by Synergize Consulting Ltd
Negotiable
Undetermined
Hybrid
Hybrid working/Hampshire, UK
Summary: The Machine Learning Engineer (SC) role involves working on a contract basis for a leading defence client, focusing on the integration of machine learning optimization with DevOps and containerization processes. The successful candidate will contribute to the development of advanced digital systems for public sector clients. This position requires a blend of technical expertise in machine learning and software engineering, along with collaboration in a hybrid working environment. Security clearance eligibility is preferred due to the nature of the work.
Key Responsibilities:
- Design, develop and optimise Machine Learning solutions using YOLO, ONNX, and NVIDIA GPU/vGPU environments.
- Lead the ML pipeline for object recognition to meet operational objectives, including tuning accuracy for specific scenarios (eg, detecting containers too high/low).
- Build and contribute to the Low-Level Design (LLD), including:
- Component breakdown and interface specifications.
- Hosting requirements (compute, GPU configuration, storage, and networking).
- Logging, monitoring (eg, rsyslog, SCOM), and system security design.
- Deliver production-quality ML software integrated into the DIS stack, with robust Ansible playbooks, unit tests, and interface controls.
- Support integration with subsystems and ensure system-wide acceptance criteria are met.
- Participate in code reviews, peer reviews, and QA cycles including static analysis tools (eg, Lint, SonarQube).
- Contribute to deliverables tracked via JIRA task management and support design updates post IT Health Check.
- Attend site visits if necessary to gather data or investigate edge case errors in Real Time ML performance.
Key Skills:
- A strong background in software engineering which includes machine learning components, and expertise in using YOLO (You Only Look Once) or similar object detection frameworks.
- Experience with NVIDIA GPU optimisation or ONNX runtime environments.
- Strong understanding of computer vision, OCR, and image/video processing.
- Proficiency in SOAP API development.
- Working knowledge of DevOps technologies including OpenShift (OCP 4.x), Kubernetes, and Cilium.
- Experience with MongoDB, Longhorn, and Zone Minder camera systems would be desirable.
- Ability to create scalable and maintainable codebases and deployment automation via Ansible.
- Development of unit tests, test plans/scripts, and validated test results in collaboration with QA teams.
- Proven experience with integration testing and documentation of interface control.
Salary (Rate): undetermined
City: undetermined
Country: UK
Working Arrangements: hybrid
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Machine Learning Engineer (SC) - Contract role - Hybrid working (Hampshire) - £competitive
Synergize Consulting are now hiring for a Machine Learning Engineer to work at a leading defence client on a contract basis.
The successful candidate will fuse machine learning optimisation with DevOps and containerisation processes to assist the team in building and developing cutting-edge digital systems for a customer in the public sector.
Key Responsibilities
- Design, develop and optimise Machine Learning solutions using YOLO, ONNX, and NVIDIA GPU/vGPU environments.
- Lead the ML pipeline for object recognition to meet operational objectives, including tuning accuracy for specific scenarios (eg, detecting containers too high/low).
- Build and contribute to the Low-Level Design (LLD), including:
- Component breakdown and interface specifications.
- Hosting requirements (compute, GPU configuration, storage, and networking).
- Logging, monitoring (eg, rsyslog, SCOM), and system security design.
- Deliver production-quality ML software integrated into the DIS stack, with robust Ansible playbooks, unit tests, and interface controls.
- Support integration with subsystems and ensure system-wide acceptance criteria are met.
- Participate in code reviews, peer reviews, and QA cycles including static analysis tools (eg, Lint, SonarQube).
- Contribute to deliverables tracked via JIRA task management and support design updates post IT Health Check.
- Attend site visits if necessary to gather data or investigate edge case errors in Real Time ML performance.
Skills & Experience Required
- A strong background in software engineering which includes machine learning components, and expertise in using YOLO (You Only Look Once) or similar object detection frameworks.
- Experience with NVIDIA GPU optimisation or ONNX runtime environments.
- Strong understanding of computer vision, OCR, and image/video processing
- Proficiency in SOAP API development.
- Working knowledge of DevOps technologies including OpenShift (OCP 4.x), Kubernetes, and Cilium.
- Experience with MongoDB, Longhorn, and Zone Minder camera systems would be desirable
- Ability to create scalable and maintainable codebases and deployment automation via Ansible.
- Development of unit tests, test plans/scripts, and validated test results in collaboration with QA teams.
- Proven experience with integration testing and documentation of interface control.
Desirable Attributes
- Strong collaboration and communication skills.
- Comfortable working in cross-functional teams and supporting peers in engineering, QA, and systems integration.
- Experience investigating and tuning ML systems in real-world or onsite environments
Due to the nature of the client, it would be an advantage for candidates to hold, or be eligible and willing to undergo, a certain level of security clearance (SC).