Systems Engineer

Silverstream Technologies
London
1 month ago
Applications closed

Related Jobs

View all jobs

Vision Systems Engineer

Systems Modelling & Simulation Engineer

Senior Systems Engineer

ADAS Engineer

Machine Learning Engineer - Hybrid Remote

Senior Machine Learning Developer - Stevenage

Job DescriptionAre you passionate about developing and maintaining core control and automation solutions? Silverstream Technologies, the market leaders in clean marine technology are looking to expand their Systems Engineering team with 2 Systems Engineers.Reporting To:

Lead Systems EngineerLocation:

Marylebone, London OR Southampton Office, including Hybrid Working.This key role is to provide Marine Control & Automation (C&A) subject matter expertise to the Silverstream Technologies business. You will be involved in a wide range of activities from developing and maintaining the core control and automation solution, applying it to projects and supporting the in-service fleet. You will also provide technical input to the strategic supply chain plans being implemented by the company.Experience / Qualifications Required:

Have you got the right qualifications and skills for this job Find out below, and hit apply to be considered.

Degree in electrical, electronic, or automation related subject.A minimum of a year working in automation and control or a similar technical discipline (ideally in the Marine industry).System integration and working on multi-discipline projects is desired.Must have experience in the design of PLC based machinery control systems including PID regulated devices, sequencing, and event-based control.Modernisation and porting of existing functionality to new platforms and/or operating systems as required is desired.Experience with network and communications protocols (e.g., Ethernet, Modbus, Profibus, NMEA) is essential.Knowledge of HMI design and modification following industry best practice is essential.Knowledge of PLC Programming on platforms following IEC 61131 is essential.Knowledge of Matlab/ Simulink or Object-oriented programming languages is essential.Excellent written and verbal communication skills.On-site commissioning experience.Good report writing and presentation skills.Good personal organisational skills.Ability to multi-task on a variety of projects to strict time scales.Understands business objectives and can influence stakeholders to meet objectives.Displays strong interpersonal skills and is accessible and approachable.Willing to travel within base country and occasionally overseas.Knowledge of marine classification society rules (DNV, ABS, LR, etc.)Benefits:

Flexi-Time with your working hoursHybrid WorkingAnnual BonusWorkplace Pension SchemeLife Assurance CoverPrivate Medical Insurance24/7 GP Access and Mental Health SupportEyecare Vouchers25 days Annual Leave + Public HolidaysCompany Sick PayDiscounted Gym MembershipHow To Apply:Email CV toInterview Process:Successful candidates will be taken through a 2 stage interview process with Silverstream:

1st Stage Interview - Via Teams.2nd Stage Interview - In Person - London HQ.Note: All successful applicants will receive contact from Faststream before submitting your CV to Silverstream.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.