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Senior/Principal ML Systems Architect (TensorFlow + Python)

SoftInWay Inc.

Bristol

On-site

GBP 150,000 - 200,000

Full time

Today
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Job summary

A leading technology company in the United Kingdom is seeking a Senior/Principal ML Systems Architect to design and implement scalable architectures for machine learning applications. This role will bridge research and production, focusing on performance optimization and cross-language integration. The ideal candidate will be experienced in TensorFlow, Python, and the latest ML technologies. Join us to work on cutting-edge solutions that impact the engineering software landscape globally.

Qualifications

  • Expertise in ML frameworks, specifically TensorFlow.
  • Strong programming skills in Python for machine learning tasks.
  • Proficient in developing APIs for integration.

Responsibilities

  • Architect the ML Solver Platform and define modular architecture.
  • Convert research code to production-ready services.
  • Implement CI/CD pipelines and ensure model lifecycle management.

Skills

Expert in TensorFlow (TF2/Keras)
Advanced Python for ML
Proficiency in gRPC/Protobuf
GPU acceleration (CUDA/cuDNN)
Metrics and tracing

Tools

TensorFlow
ONNX Runtime
FastAPI
Job description
Senior/Principal ML Systems Architect (TensorFlow + Python)
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.
  • Convert research code into robust, testable, and observable services.
  • Implement CI/CD pipelines, automated testing, and reproducibility standards.
  • 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.
  • APIs: Proficiency in gRPC/Protobuf and REST for cross-language integration.
  • 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.
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.

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