At a Glance
- Tasks: Design and implement scalable ML architecture for production systems using TensorFlow and Python.
- Company: Join a leading tech firm focused on innovative machine learning solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborate with top professionals in a dynamic and supportive environment.
- Why this job: Be at the forefront of ML technology and make a significant impact in commercial software.
- Qualifications: Expertise in TensorFlow, Python, and experience with APIs and performance optimisation.
The predicted salary is between 72000 - 108000 £ per year.
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.
Principal Machine Learning Engineer – Production Systems in Bristol employer: SoftInWay Inc
SoftInWay Inc offers an exceptional work environment in Weston-super-Mare, where innovation meets collaboration. As a Rotor Dynamics Solver Developer, you'll benefit from a supportive culture that prioritises employee growth through hands-on experience and mentorship, while contributing to cutting-edge software solutions in turbomachinery. Join us for a rewarding career that not only enhances your technical skills but also fosters a sense of community and purpose.
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We think this is how you could land Principal Machine Learning Engineer – Production Systems in Bristol
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We think you need these skills to ace Principal Machine Learning Engineer – Production Systems in Bristol
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at SoftInWay Inc.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at SoftInWay Inc and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at SoftInWay Inc
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If SoftInWay Inc uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
