Algorithm Developer

Experis UK
Edinburgh
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist, algorithm development

Research Software Engineer

Full Stack Developer - Computer vision

Senior Machine Learning Developer - Stevenage

Systems Modelling & Simulation Engineer

Analytics Engineering Manager

Job Title: Audio DSP Developer / Algorithm Developer

Location: United Kingdom

Outside IR35 Contract

Rate: To be discussed

Duration: minimum 12+ months (initial 6 months)

We want to speak to experienced DSP engineers with prior experience in the defence space. You'll ideally have prior SC clearance, but at the very least be a sole British national. Our client is a leader within their space with offices around the UK mainly within the north and south-west of the country.

Key Responsibilities:

  • Design, develop, and implement digital signal processing algorithms for sonar systems.
  • Analyse and interpret sonar data to improve system performance and accuracy.
  • Collaborate with cross-functional teams to integrate DSP solutions into sonar hardware and software.
  • Conduct testing and validation of DSP algorithms in both lab and field environments.
  • Troubleshoot and resolve issues related to signal processing and system performance.
  • Stay updated with the latest advancements in DSP and sonar technologies.

Qualifications:

  • Bachelor's or Master's degree in Electrical Engineering, Computer Science, or a related field.
  • Strong background in digital signal processing, particularly in Audio / Sonar.
  • Proficiency in programming languages such as MATLAB, Python, or C/C++.
  • Experience with signal processing tools and software.
  • Excellent problem-solving skills and attention to detail.
  • Ability to work effectively in a team environment and communicate technical concepts clearly.
  • Knowledge of machine learning techniques applied to signal processing.
  • Familiarity with hardware implementation of DSP algorithms.

Security Requirements:

  • Candidates must be sole British nationals.
  • Ideally, candidates should have prior SC (Security Clearance).

Preferred Skills and Experience:

  • Experience with underwater acoustics and sonar system design.

Candidates with solid acoustic DSP engineer backgrounds will be considered for this role also. It also is worth mentioning that we work with a number of businesses within this space, and that number will only increase. If this role isn't right we almost certainly have another for you.

Due to the nature of work that this client carries out, this role should be considered onsite, which locations will be discussed on the phone when we speak.

People Source Consulting Ltd is acting as an Employment Business in relation to this vacancy. People Source specialise in technology recruitment across niche markets including Information Technology, Digital TV, Digital Marketing, Project and Programme Management, SAP, Digital and Consumer Electronics, Air Traffic Management, Management Consultancy, Business Intelligence, Manufacturing, Telecoms, Public Sector, Healthcare, Finance and Oil & Gas.


JBRP1_UKTJ

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.