Staff Software Engineer in London
Staff Software Engineer

Staff Software Engineer in London

London Full-Time 60000 - 84000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead engineering efforts for personalisation models serving 300+ million users.
  • Company: Join ShareChat, India's largest homegrown social media platform with a vibrant culture.
  • Benefits: Flexible remote work, competitive salary, and opportunities for growth and development.
  • Why this job: Make a real impact on user engagement with cutting-edge ML technology.
  • Qualifications: 8+ years in engineering, strong coding skills, and experience with large-scale ML solutions.
  • Other info: Exciting opportunity to shape the future of recommendation systems in a dynamic environment.

The predicted salary is between 60000 - 84000 £ per year.

Who are we and What do we do?

ShareChat (Mohalla Tech Pvt Ltd) is India’s largest homegrown social media company and the only local player to achieve profitability in the industry, with 200+ million Monthly Monetizable Users across all its platforms. Founded in 2015, ShareChat has social media brands such as the ShareChat App and Moj App and micro drama app QuickTV under its portfolio. QuickTV, the newest addition to ShareChat's family of apps, crossed the 10 million downloads mark within 3 months of launch and currently has 60Mn MAUs across the network viewing the vertical episodic content. Today, the ShareChat network maintains a whopping 1,000 Cr ARR and is India’s leading social media platform servicing users across the country in 15 regional languages. This growth has led to a 28% YoY revenue growth in the July-Sept (2025-26) quarter and increased it by more than 60% in the Oct-Dec quarter.

What does the team do?

Serving recommendations to 300+ million users entails developing large scale personalization and recommendation models that understand user needs and preferences in real-time, while also helping 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, causal inference, optimization, ranking and recommendation.

What You’ll Do

Within the Sharechat AI team, we are looking for an experienced Staff engineer to lead the engineering efforts around serving personalization models efficiently at scale, leading efforts across 10+ MLEs, SDEs 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 in order to drive up user retention and engagement while minimizing server and cloud costs of serving large scale models, 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?

  • 8+ years of industry experience with a solid understanding of engineering, infrastructure and ML best practices.
  • Strong coding skills with Go or Java.
  • Design and help develop systems that serve recommendations to over 300 million users.
  • Drive engineering roadmap creation and execution, specifically around feed ranking and recall oriented candidate generation systems.
  • Provide technical guidance in ranking systems design, implementation & experimentation, and take end to end ownership of ML systems, and key user satisfaction based metrics.
  • Drive architectural strategy and design for complex ML systems that support the needs of users, creators and content stakeholders.
  • Familiarity with cloud platforms such as AWS, Google Cloud, or Azure. Knowledge of containerization and orchestration tools like Docker and Kubernetes is a plus.
  • Experience designing end to end ML data pipelines.
  • Experience with database technologies such as PostgreSQL, MySQL, or MongoDB, Spark, Databricks and stream data processing such as Kafka, RedPanda is a plus.
  • Direct experience in building and applying large-scale (100M+ users) machine learning solutions for personalizing recommendations.
  • Hands-on experience building training frameworks and/or serving large-scale models using tools such as Tensorflow or PyTorch is a plus.
  • You stay up-to-date with the state-of-the-art open source infrastructure solutions applicable to designing and improving large scale recommender systems, data engineering, and machine learning.
  • You have a Master’s or PhD in Computer Science, statistics, or an engineering field with 5+ years of experience.

Where will you be?

London (Remote)

What’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.

Staff Software Engineer in London employer: ShareChat

ShareChat is an exceptional employer, offering a dynamic work culture that prioritises innovation and employee growth. With a commitment to flexibility and professional development, employees are empowered to take ownership of their projects while contributing to cutting-edge technology that serves over 300 million users. Located in London, the company fosters a collaborative environment where top talent thrives, making it an ideal place for those seeking meaningful and rewarding careers in the tech industry.
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Contact Detail:

ShareChat Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Staff Software Engineer in London

✨Tip Number 1

Network like a pro! Reach out to current employees at ShareChat on LinkedIn or other platforms. A friendly chat can give you insider info and might just get your foot in the door.

✨Tip Number 2

Prepare for technical interviews by brushing up on your coding skills, especially in Go or Java. Practice common algorithms and data structures, and don’t forget to showcase your experience with ML systems!

✨Tip Number 3

Showcase your passion for recommendation systems! Be ready to discuss your previous projects and how they relate to personalisation and user engagement. We love seeing candidates who are genuinely excited about our work.

✨Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining the ShareChat family.

We think you need these skills to ace Staff Software Engineer in London

Machine Learning
Personalization Models
Deep Learning
Causal Inference
Optimization
Ranking Systems
Recommendation Systems
Go Programming
Java Programming
Cloud Platforms (AWS, Google Cloud, Azure)
Containerization (Docker)
Orchestration (Kubernetes)
ML Data Pipelines
Database Technologies (PostgreSQL, MySQL, MongoDB)
Stream Data Processing (Kafka, RedPanda)
TensorFlow
PyTorch

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Staff Software Engineer role. Highlight your expertise in ML, coding languages like Go or Java, and any relevant projects you've worked on that demonstrate your ability to handle large-scale systems.

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about recommendation systems and how your background makes you a perfect fit for our team. Don’t forget to mention specific achievements that showcase your problem-solving skills.

Showcase Your Projects: If you've worked on any significant projects related to machine learning or recommendation systems, make sure to include them in your application. We love seeing real-world applications of your skills, so share links or descriptions that highlight your contributions.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re genuinely interested in joining our team at ShareChat!

How to prepare for a job interview at ShareChat

✨Know Your Stuff

Make sure you brush up on your knowledge of machine learning, recommendation systems, and the specific technologies mentioned in the job description. Be ready to discuss your experience with large-scale ML solutions and how you've tackled similar challenges in the past.

✨Showcase Your Leadership Skills

As a Staff Software Engineer, you'll be expected to lead teams and projects. Prepare examples of how you've successfully guided teams in the past, especially in engineering roadmaps or complex ML system designs. Highlight your ability to mentor others and drive results.

✨Understand Their Values

Familiarise yourself with ShareChat's core values: Ownership, Speed, User Empathy, Integrity, and First Principles. Think of ways you've embodied these values in your previous roles and be ready to share those stories during the interview.

✨Ask Insightful Questions

Prepare thoughtful questions about the team’s current projects, challenges they face, and their vision for the future. This shows your genuine interest in the role and helps you assess if the company culture aligns with your own values and work style.

Staff Software Engineer in London
ShareChat
Location: London

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