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

Nominate & Attend

Staff Machine Learning Engineer

ShareChat
united kingdom of great britain and northern ireland, uk
1 month ago
Applications closed

Related Jobs

View all jobs

Staff Machine Learning Engineer

Machine Learning Engineer - Fixed Term Contract

Junior Machine Learning Engineer - AI startup

Staff Data Scientist

Staff AI Engineer – Computer Vision & ML

Principal Data Engineer

Staff Machine Learning EngineerWho are we and What do we do?ShareChat (https://sharechat.Com/about) is India's largest homegrown social media company, with 325+ million monthly active users across all its platforms including Moj, a leading short video app which was launched in a record 30 hours in 2020. It's just another way we, as a team, turn ideas into reality, and you can do it too!Founded in October 2015, with a vision of building an inclusive community that encourages & empowers each individual to share their unique journey and valuable experiences with confidence. We are spearheading India's internet revolution by building products through world-class AI & tech to evangelize the content ecosystem for India in regional languages.We believe in complete ownership of problem-solving while committing to speed and integrity in everything we do. We place the utmost importance on user empathy & strive to work towards creating a world-class experience for them every day. Join us to drive how the next billion users will interact on the internet!What does the team do? Serving recommendations to 300 million users entails developing large scale personalization and recommendation models that not only understand user needs and preferences, but also help 100 million+ creators grow their audiences on our platforms. A subset of the problems we tackle include:Serving personalized feeds for 300+ million users via real-time candidate generators, multi-task prediction models, whole-page optimization, and in-session personalization.Nurturing our content and creator ecosystem, and developing models for strategic content valuation.Multi-objective balancing and long term measurement.We rely extensively on state-of-the-art ML around personalization, deep learning, bandits, causal inference, optimization, ranking and recommendation.AI - Our AI teams are spearheading the research and development, presenting innovations at various conferences. Click here to learn.Learn from our CEO Ankush about our culture, innovation and growth. Click here.What You’ll Do? Within the Sharechat AI team, we are looking for an experienced Staff ML engineer to lead the ML efforts around improving personalization models, leading efforts across 10+ MLEs and decision scientists working on feed ranking and candidate generation systems that power Sharechat’s recommender systems. In this role you will help us further improve our recommendation systems, and act as a subject matter expert in the recommender systems and ML ranking domains.You would be joining us at an exciting time! The science behind recommendation systems is rapidly changing, and we’re making big progress at a rapid pace.Who are you?Design and help develop systems that serve recommendations to over 300 million usersDrive ML roadmap creation and execution, specifically around feed ranking and recall oriented candidate generation systemsProvide technical guidance in ML model formulation, implementation & experimentation, and take end to end ownership of ML systems, and key user satisfaction based metricsDrive architectural strategy and design for complex ML systems that support the needs of users, creators and content stakeholdersPreferred QualificationsHands-on experience training and serving large-scale models using frameworks such as Tensorflow or PyTorchExperience productionising machine learning models, and managing and designing end to end ML systems, and data pipelinesDeep understanding of the mathematical foundations of Machine Learning algorithmsDirect experience in building and applying large-scale (100M+ users) machine learning solutions for feed ranking, and personalizing recommendations.You stay up-to-date with the state-of-the-art technology in the domains of recommender systems, data engineering, and machine learning. Relevant publications in top tier applied machine learning conferences is a plusYou have a Master’s or PhD in ML, statistics, or an engineering field with 8+ years of experienceWhere you’ll be?Fully remote within the UK or a European time zone.Know more about us:AI @ ShareChat | AI Projects @ ShareChat/Our BlogWhat's in it for you?At ShareChat, our values - Ownership, Speed, User Empathy, Integrity, and First Principles - are at the core of our ways of working. We believe in hiring top talent and grooming future leaders by providing a flexible environment to aid growth and development. We also offer several benefits to our employees - like ESOPs, remote working, monthly childcare allowance for women employees, insurance coverage, and more.

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.