At a Glance
- Tasks: Lead ML strategy, develop recommendation systems, and ensure platform safety.
- Company: Join ShareChat, India's top social media platform with 325 million users and a $5 billion valuation.
- Benefits: Enjoy remote work, career growth opportunities, and employee-centric perks like ESOPs and childcare allowance.
- Why this job: Make a real impact in AI-driven content creation while collaborating with top talent globally.
- Qualifications: 10+ years in ML, expertise in large-scale systems, and a Master's or PhD in relevant fields.
- Other info: Work in a culture that values innovation, collaboration, and continuous learning.
The predicted salary is between 57600 - 84000 £ per year.
Who are we and What do we do? From the humble idea of giving all regional languages a stage to successfully building India's No.1 social media platform, we've journeyed to turn ideas into reality. At ShareChat and Moj, our short video platform, we have over 325 million users, 80 million creators, and over 2.5 billion monthly shares. Valued at $5 billion, ours is a story of disrupting the digital narrative as we build Bharat’s content creation ecosystem. An open, honest culture and our values, such as first principles, speed, integrity, user-centricity, and ownership, drive our teams to innovate our products every day. We are on the path to establishing ShareChat as the world's largest AI-centered social media platform. We are thrilled to offer you the opportunity to solve complex problems at scale, learn with the best minds, pursue unstoppable growth, and, most importantly, make a far-reaching impact. Join us to revolutionize Bharat’s content creation ecosystem powered by AI & ML. Scaling ideas to reality is how we do our business!
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:
- Create personalized feeds for 300+ million users via real-time candidate generators, multi-task prediction models, whole-page optimization, and in-session personalization.
- Nurturing our 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.
What You’ll Do? As a Principal Machine Learning Engineer in the ShareChat AI team, you will play a pivotal role in defining and executing the ML strategy across key business domains. You will serve as one of the senior-most individual contributors in machine learning, with opportunities to lead and contribute to multiple high-impact areas such as:
- Recommendation Systems: Deliver a world-class personalized user experience by driving innovations in feed ranking and content recommendation.
- Trust & Safety: Safeguard the platform using advanced multi-modal models and behavior modeling & network analysis.
- Advertising Models: Ensure sustained revenue growth by building models that optimize advertiser satisfaction without compromising user experience.
- Technical Leadership: Set the standard for engineering excellence and guide the organization in adopting state-of-the-art machine learning techniques and tools.
You will work with cross-functional teams, collaborating closely with 10+ Machine Learning Engineers and Decision Scientists. Your primary focus will be advancing state-of-the-art personalized recommendation and ranking models that impact over 300 million users globally.
Who you are:
- Hands-on Expertise: Proven experience training, fine-tuning, and deploying large-scale machine learning models using TensorFlow, PyTorch, or similar frameworks.
- Systems Thinking: Deep experience in designing, managing, and productionizing ML pipelines, handling end-to-end machine learning systems, including data engineering, model training, and real-time inference.
- Domain Mastery: Specialization in large-scale (100M+ users) content recommendation systems, feed ranking, behavior modeling and network analysis in trust & safety. Demonstrated ability to balance competing metrics, such as maximizing advertiser ROI while maintaining high user engagement. Skilled in multi-objective optimization and AB testing frameworks.
- Thought Leader in ML: Recognized expertise with publications in top-tier applied machine learning conferences or significant contributions to the recommender systems community.
- Mentor and Influencer: A proven track record of guiding and upskilling ML teams, fostering a culture of collaboration, innovation, and accountability.
- Continuous Learner: Stay updated with cutting-edge advancements in recommender systems, machine learning, and AI, ensuring the organization is at the forefront of technological evolution.
Preferred Qualifications:
- Hands-on experience in building, distributed training and serving of large-scale models using frameworks such as Tensorflow or PyTorch.
- Deep understanding of the mathematical foundations of Machine Learning algorithms.
- Expertise in building and applying large-scale (100M+ users) machine learning solutions for content feed ranking and personalizing recommendations.
- Expertise in NLP, Vision, behavior modeling and network analysis.
- Key skills for the advertising domain (predictive modeling (CTR/CVR), multi-objective optimization, auction dynamics and behavioral targeting) is a plus.
You have a Master’s or PhD in ML, statistics, or an engineering field with 10+ years of industry experience in machine learning, including at least 5 years in large-scale systems for user engagement, personalization, or similar domains.
Where you’ll be? Remote, UK / EU
Why join ShareChat? We believe in creating economic opportunities for our content creators as a shared purpose. Join us to make a tangible impact for regional Indian audiences. Grab an opportunity to solve complex problems powered by our AI and ML recommendation system for over 325 million monthly active users, 80 million creators and key partners. Drive your career growth through our upskilling programs, accelerated by values like speed and ownership. You get a chance to work with top talent across the globe in a collaborative and learning culture. Experience growth in a people-first organisation with unparalleled rewards and employee-centric policies, including ESOPs, monthly childcare allowance, insurance, and more.
Principal Machine Learning Engineer (Basé à London) employer: Golden Bees
Contact Detail:
Golden Bees Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Machine Learning Engineer (Basé à London)
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning, particularly in recommendation systems and personalisation. Being able to discuss recent advancements or case studies during your interview can demonstrate your passion and expertise in the field.
✨Tip Number 2
Network with current employees or industry professionals who have experience in large-scale ML systems. Engaging in conversations about their work at ShareChat can provide you with valuable insights and potentially useful connections.
✨Tip Number 3
Prepare to showcase your hands-on experience with frameworks like TensorFlow or PyTorch. Be ready to discuss specific projects where you've successfully implemented large-scale models, as this will highlight your practical skills and problem-solving abilities.
✨Tip Number 4
Demonstrate your leadership qualities by sharing examples of how you've mentored others in the field of machine learning. Highlighting your ability to foster collaboration and innovation can set you apart as a candidate who aligns with ShareChat's values.
We think you need these skills to ace Principal Machine Learning Engineer (Basé à London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly with large-scale systems and recommendation models. Use specific examples that demonstrate your hands-on expertise with frameworks like TensorFlow or PyTorch.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and ML, and how your background aligns with ShareChat's mission. Mention specific projects or achievements that showcase your ability to solve complex problems and lead teams.
Showcase Your Thought Leadership: If you have publications or significant contributions to the machine learning community, be sure to include them. This demonstrates your expertise and commitment to staying at the forefront of technological advancements.
Highlight Collaboration Skills: Since the role involves working with cross-functional teams, emphasise your experience in mentoring and collaborating with other engineers and scientists. Provide examples of how you've fostered a culture of innovation and accountability in previous roles.
How to prepare for a job interview at Golden Bees
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with machine learning frameworks like TensorFlow and PyTorch. Highlight specific projects where you've trained, fine-tuned, and deployed large-scale models, as this role demands a deep understanding of these technologies.
✨Demonstrate Systems Thinking
Illustrate your ability to design and manage end-to-end ML pipelines. Discuss how you've handled data engineering, model training, and real-time inference in previous roles, as this is crucial for the position.
✨Prepare for Domain-Specific Questions
Expect questions related to content recommendation systems and user engagement metrics. Be ready to explain your experience with multi-objective optimization and AB testing frameworks, as these are key components of the job.
✨Exhibit Leadership and Mentorship Skills
Share examples of how you've guided and upskilled teams in the past. This role requires not just technical skills but also the ability to foster collaboration and innovation within the team.