National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Machine Learning Engineer, Trilogy (Remote) - $100,000/year USD

Crossover
Chelmsford
7 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer - Bioimage Data & Agentic Systems

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer Trainer

Machine Learning Engineer - Up to £150k + Equity

Ready to leverage your mastery of LLMs to drive productivity? At Trilogy, we're opening doors to an exceptional tech career, welcoming those who've honed their AI skills to elevate their expertise in a dynamic environment. We're offering a rare chance where your primary focus will be to further expand your proficiency in LLMs.

In an industry often filled with more buzzwords than tangible progress, Trilogy stands out as a hub of genuine innovation. Our focus is on practical, real-world applications aimed at reshaping industries. Imagine creating AI-driven tools that streamline workflow, automate tasks, or enhance decision-making processes, all to significantly boost productivity.

Your mandate? Harnessing LLMs to revolutionize how businesses operate, improving efficiency and effectiveness. You'll be architecting solutions that integrate AI seamlessly, making intricate processes more accessible and refining workflows for maximum output. Here, you won't be lost in bureaucratic hurdles or pitching ideas into the void. Instead, you'll witness the direct impact of your efforts, as your work directly influences the evolution of productivity tools.

Ready to unleash your expertise and become a force of change? Let's explore if you're the catalyst we're seeking for this exciting opportunity!


What you will be doing

  • Designing and building high-quality AI automations to streamline processes, enhance productivity, and deliver robust, scalable solutions across diverse applications
  • Experimenting with state-of-the-art AI tools like GPT-4 Vision and Amazon CodeWhisperer, integrating them into our developmental process to assess and enhance their utility
  • Evaluating and optimizing the implementation of AI solutions across various infrastructures, including AWS, to ensure seamless performance and integration


What you will NOT be doing

  • Traditional coding - our AI does the heavy lifting, freeing you to innovate and strategize
  • Being stuck on repetitive tasks - no two problems are the same


Key Responsibilities

Architecting and deploying sophisticated, fully-automated AI systems that require zero human intervention for a truly scalable impact


Candidate Requirements

  • Advanced generative AI proficiency (i.e., use of multiple AI tools, ability to automate workflows and custom GPTs); if you've only used LLMs for research, learning, brainstorming, or content generation, that will be deemed insufficient
  • At least 3 years of professional work experience
  • Proficiency in Python and API integration
  • Proficiency in AWS


National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.