Principal machine learning engineer – production systems Work, Jobs in Bedwas, Cay (with Salaries)

Principal Machine Learning Engineer – Production Systems
SoftInWay Inc. —Weston-super-Mare
- Machine learning
- APIs
- Python

Check out these similar jobs

Based on your search for principal machine learning engineer – production systems jobs.

Principal Machine Learning Engineer – Production Systems
SoftInWay Inc. —Weston-super-Mare
Security: SBOM, image signing, role-based access, vulnerability scanning. We are seeking a highly experienced ML Systems Architect to design and implement a…
Principal Data Architect
Toumetis —Bristol
Contribute to solution design with clients, including pre-sales, technical presentations, and strategy sessions. This is not a pure strategy role.
Quick apply
3d

I want to receive the latest job alerts for principal machine learning engineer – production systems in bedwas, cay

By signing in to your account, you agree to SimplyHired's Terms of Service and consent to our Cookie and Privacy Policy.

Explore jobs in more locations

principal machine learning engineer – production systems jobs near bedwas, cay

Machine Learning Engineer jobs in Manchester

Machine Learning Engineer jobs in Durham

Machine Learning Engineer jobs in Marine

Machine Learning Engineer jobs in Liverpool

Learning Development jobs in Cornwall

Learning Support Assistant jobs in Basingstoke

Learning Support Assistant jobs in London

Principal Machine Learning Engineer – Production Systems

SoftInWay Inc.
Weston-super-Mare

Apply Now

Job details

Qualifications

TensorFlow
Kubernetes
PyTorch
C#
.NET
Docker
Machine learning
REST
GitHub
APIs
Keras
gRPC
GitLab
Python

Full job description

Overview

We are seeking a highly experienced ML Systems Architect to design and implement a scalable, production-grade architecture for our machine learning solver. This role bridges research prototypes and commercial deployment, ensuring reliability, maintainability, and performance in a mixed technology stack.

Responsibilities

Architect the ML Solver Platform:
- Define modular architecture for data preprocessing, model execution, and post-processing.
- Establish clear API contracts between Python/TensorFlow and C# services.
Productionize ML Workflows:
- Convert research code into robust, testable, and observable services.
- Implement CI/CD pipelines, automated testing, and reproducibility standards.
Integration & Interoperability:
- Design REST/gRPC endpoints for cross-language communication.
- Ensure compatibility with C#/.NET services.
Performance & Scalability:
- Optimize GPU/CPU utilization, batching strategies, and memory management.
- Plan for multi-model and multi-tenant scenarios.
MLOps & Lifecycle Management:
- Implement model versioning, artifact registries, and deployment workflows.
- Set up monitoring, logging, and alerting for solver performance.
Security & Compliance:
- Apply best practices for secrets management, dependency scanning, and secure artifact storage.

Required Skills & Experience

ML Frameworks: Expert in TensorFlow (TF2/Keras), experience with ONNX Runtime for inference.
Programming: Advanced Python for ML; strong understanding of packaging, type checking, and performance profiling.
Architecture: Proven experience designing scalable ML systems for production.
APIs: Proficiency in gRPC/Protobuf and REST for cross-language integration.
MLOps: CI/CD pipelines, containerization (Docker/Kubernetes), model registries, reproducibility.
Performance Optimization: GPU acceleration (CUDA/cuDNN), mixed precision, XLA, profiling.
Observability: Metrics, tracing, structured logging, dashboards.
Security: SBOM, image signing, role-based access, vulnerability scanning.

Preferred Qualifications

Experience with ONNX Runtime Training, PyTorch, or hybrid ML architectures.
Familiarity with distributed training strategies and multi-GPU setups.
Knowledge of feature stores and data validation frameworks.
Exposure to regulated environments and compliance frameworks.

Tools & Technologies

ML: TensorFlow, ONNX Runtime, tf2onnx.
APIs: FastAPI, gRPC.
DevOps: GitLab CI/GitHub Actions, Docker, Kubernetes.
Monitoring: Prometheus, Grafana, OpenTelemetry.
Security: HashiCorp Vault, Sigstore.

Why Join Us?

Work on cutting-edge ML solutions integrated into commercial engineering software.
Define architecture that scales across global deployments.
Collaborate with a team of experts in ML, software engineering, and UI development.

To apply: Send your resume and a brief cover letter to [email protected]

Apply Now

Refine Your Search

principal machine learning engineer – production systems jobs in bedwas, cay