Senior/Principal ML Systems Architect (TensorFlow + Python)

We’re hiring a Senior ML Systems Architect to lead the design of our TensorFlow-based solver for commercial applications. You’ll define scalable architecture, ensure production readiness, and integrate ML with C# services. Must have deep expertise in TensorFlow, Python, and MLOps. Apply now to shape the future of ML in engineering software. ​​​​​​​​​​​​​​

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.

Location: Remote or on-site for UK Employment
Type: Full-time
Level: Senior/Principal