Senior/Principal ML Systems Architect (TensorFlow + Python) in IK Aktualnaya Mehanika, OOO

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. 

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

Posting Snippet 

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.