Operations Technician (Landfill Gas)

First Military Recruitment
Blackburn
2 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Pensions System Calculation and Data Analyst

Director of Data Science & AI – Global Manufacturing Transformation

Data Scientist

Estimator

Data & Insights Analyst

MS560 - Operations Technician (Landfill Gas)

Location:Blackburn

Salary:£35,378 to £40,887 per annum + company vehicle & benefits.

Overview:First Military Recruitment are currently seeking an Operations Technician on behalf of one of our clients.

The successful candidate will be responsible for being under the supervision of the Area Manager, you will complete the day to day operations of the gas field and generators at the assigned sites in order to achieve maximum electrical output, whilst maintaining the highest levels of safety. The ideal candidate will have a strong mechanical or electrical bias and ideally located Northern Manchester through to Blackburn & East to Bradford/Leeds.

The role has will include an on-call duty, one in five weeks, covering sites in Durham, Doncaster & Fleetwood.

Our client encourages applications from ex-military personnel however all candidates will be given due consideration.

Duties and Responsibilities:

  • Ensure that safe working practises and procedures are adhered to within all areas of work.
  • Assist with the implementing and supervising of health, safety and quality procedures at sites.
  • Assist with planned, preventative and breakdown maintenance of the generator sets and all other associated plant and equipment.
  • Provide backup and call out assistance to Operations Technicians at other sites.
  • Complete accurate and concise record keeping of operations and maintenance.
  • Ensure required gas field readings are made and issued on time to relevant personnel.
  • Assist in the ordering of consumable parts items, including, lube oils, filters, spark plugs, fan belts, etc.
  • Maintain adequate spare parts stock on assigned sites.
  • Carry out routine stock takes of parts at site.
  • Position is Monday to Friday- 8am to 5pm with an hour for lunch.
  • On-Call (once fully trained) - one in three/four weeks.
  • Van supplied (reportable via HMRC).

Skills and Qualifications:

  • The successful candidate will have operations and maintenance experience, with reciprocating engines and/or the relating control systems.
  • Be qualified to BTEC level or equivalent, preferably in a mechanical discipline or proven previous experience.
  • This position requires a high degree of flexibility, self-motivation, initiative, the ability to work well as part of a team and at times work alone.
  • This position has an On-Call requirement.


JTRA1_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.