Компания "Передовые цифровые решения"
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
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