hackajob is partnering directly with Zaizi to hire for this role. Role Overview Dept: Applied AI Team Term: Permanent Location: Cheltenham DV Clearance: Required & British Work on exciting public sector projects and make a positive difference in peoples lives. At Zaizi, we thrive on solving complex challenges through creative thinking and the latest tools and tech. As a Machine Learning Implementation Engineer, youll be responsible for taking AI models and algorithms from the research phase and maturing them into robust, production-ready software. Your focus is on increasing the Technology Readiness Level (TRL) of our AI solutions, ensuring they are scalable, reliable, and effectively integrated into business workflows to automate tasks and gain insights from data. Key responsibilities include refining model code for performance, ensuring software maturity, and solving complex technical hurdles during the transition from prototype to product. You will influence technical decisions within the team, mentor junior members, and handle complex, non-routine problems. Our work culture is inclusive, modern, friendly, and democratic. We look for bright, positive-thinking individuals with a can-do attitude. Our people enjoy challenging themselves to be the best at what they do if that sounds like you, you'll fit right in! Requirements Role Objectives These are the expected objectives for this role. We are happy to discuss this further during the interview process with the successful candidate. ? Model Maturation & Delivery: Design, build, and refactor complex machine learning models, ensuring they move from experimental stages to high- quality, high-performance production software. ? Software Engineering for AI: Take the output from research activities and "harden" the software to achieve higher TRLs suitable for deployment in the National Security Domain. ? System Integration: Design and manage the integration of ML models into broader software architectures, ensuring stability and performance. ? Edge Optimization & Deployment: Adapt and optimize machine learning models for resource-constrained environments, ensuring high- performance execution on edge hardware, including Android-based mobile devices. ? Technical Excellence: Stay current with AI implementation best practices to ensure our solutions are maintainable and scalable. Skills & Experience ? Technical Expertise: Broad technical expertise in machine learning, demonstrating a deep understanding of ML algorithms, frameworks, and software engineering best practices. ? Model Maturation: Proven experience in taking research-grade AI/ML code and maturing it into production-ready software. ? Technology Implementation: Ability to evaluate new generative AI technologies for business relevance and feasibility, focusing on practical implementation within the National Security Domain. ? Advanced Prototyping: Delivering robust proofs of concept that bridge the gap between initial research and final application. ? Specialist Advice: Serving as a key technical resource for the practical application of generative AI within the organization. ? Data Science: Applying a range of data science techniques to support model refinement and software hardening. ? Deployment Experience: Proven experience in building and deploying complex machine learning models into live environments. Nationality Due to UK government security restrictions, you will need to be a British Citizen and have been resident in the UK for the last ten years to apply for this role. Benefits Compensation Competitive Pay: Salaries reviewed annually to ensure they reflect your performance and market value. Loyalty Pension: We invest in your future. Starting at a 5% employer contribution, we increase this by 0.5% every year after your third anniversary, up to a maximum of 8% . Protection: Comprehensive Group Life Assurance for peace of mind. Purpose & Culture Real Impact: Work on mission-critical projects that secure and improve the UK's digital infrastructure. Autonomy: A culture that empowers you to make decisions, prototype rapidly, and iterate towards success. Service & Community: We support those who serve. 10 paid days for Reservist Military Service. Work / Life Balance Time Off: 25 days annual leave + Bank Holidays, with the flexibility to Buy/Sell additional days to suit your lifestyle. Giving back: 2 paid volunteering days per year. Development & Growth Master Your Craft: Fully funded professional certifications (AWS, GCP, Agile, etc.) supported by 5 days paid study leave . Expand Your Horizons: An additional Β£500 annual "Personal Choice" fund to learn whatever inspires youwork-related or not. Support: Access to 1-2-1 professional coaching and team training to accelerate your career. Health & Balance Premium Health: Vitality Private Medical Insurance (includes Apple Watch, gym discounts, and rewards). Flexibility: Genuine hybrid working with a WFH equipment allowance to perfect your home setup. Wellbeing: Cycle to Work scheme and a commitment to sustainable, healthy working practices. For further information contact: TPBN1_UKTJ
Machine Learning Implementation Engineer, AI (SFIA4) employer: Hackajob Ltd
JPMorgan Chase is an exceptional employer, offering a dynamic work environment where innovation and collaboration thrive. As a Lead Site Reliability Engineer, you will not only tackle complex challenges but also benefit from extensive professional development opportunities and a strong commitment to diversity and inclusion. Located in a global financial hub, you'll be part of a team that values your expertise and encourages a culture of continuous improvement and technical excellence.