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- Tasks: Design and implement scalable ML architectures for cutting-edge solutions.
- Company: Join SoftInWay UK Ltd, a leader in innovative engineering software.
- Benefits: Enjoy competitive salary, great benefits, and the chance to work remotely.
- Why this job: Make a real impact by bridging research and commercial deployment in ML.
- Qualifications: Expertise in TensorFlow, Python, and scalable ML systems required.
- Other info: Collaborate with top experts and enjoy excellent career growth opportunities.
The predicted salary is between 54000 - 84000 £ per year.
SoftInWay UK Ltd. is 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.
- Competitive salary and benefits.
To apply: Send your resume and a brief cover letter to HR@softinway.com
Principal Machine Learning Engineer - Production Systems in England employer: SoftInWay UK Ltd.
Contact Detail:
SoftInWay UK Ltd. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Machine Learning Engineer - Production Systems in England
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ML systems. It’s a great way to demonstrate your expertise beyond the written application.
✨Tip Number 3
Prepare for interviews by brushing up on common ML system design questions. Practice explaining your thought process clearly and confidently – it’s all about showing how you think!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Principal Machine Learning Engineer - Production Systems in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with ML frameworks like TensorFlow and your skills in Python. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Principal Machine Learning Engineer position and how your expertise can help us build scalable ML systems. Keep it concise but impactful!
Showcase Your Projects: If you've worked on any interesting ML projects, make sure to mention them! We love seeing real-world applications of your skills, especially if they involve production systems or CI/CD pipelines.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at SoftInWay UK Ltd.
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially TensorFlow, Python, and C#. Brush up on your knowledge of APIs like gRPC and REST, as well as CI/CD practices. Being able to discuss these confidently will show that you’re ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, particularly around productionising ML workflows or optimising performance. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easy for the interviewer to follow your thought process.
✨Demonstrate Your MLOps Knowledge
Since this role involves MLOps, be ready to talk about your experience with model versioning, deployment workflows, and monitoring. Bring examples of how you’ve implemented CI/CD pipelines or used tools like Docker and Kubernetes in past projects to illustrate your expertise.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company’s approach to ML architecture, their current projects, or how they handle security and compliance. This not only shows your interest but also helps you gauge if the company is the right fit for you.
