Digital Marketer

Required Experience: 10–15 years (with at least 3–5 years in leadership roles)

● 10–15 years of overall experience in backend engineering, with strong exposure to

Python and/or Golang.

● 3–5 years of experience managing engineering teams.

● Proven experience delivering large-scale, distributed systems in production

environments.

● Strong understanding of microservices, cloud-native architecture, and DevOps

practices.

● Hands-on background in backend engineering (able to guide teams technically, even

if not coding daily).

● Familiarity with CI/CD pipelines, observability, and performance optimization.

● Experience in financial services or high-transaction domains is a plus.

● Experience leading teams that have utilized AI-driven development practices (e.g.,

agentic coding, LLM integration) to improve productivity and innovation is a

significant advantage.

Skills

● Excellent leadership and people management abilities.

● Strong communication and stakeholder management skills.

● Ability to balance technical depth with business priorities.

● Problem-solving mindset with a focus on delivery and impact.

● Passion for building engineering culture and improving developer experience.

Duties

About Us:

We are a UK-based conveyancing firm dedicated to transforming property transactions through cutting-edge artificial intelligence. We are seeking a talented Machine Learning Engineer with 1–2 years of experience to join our growing AI team. This role offers a unique opportunity to work on scalable ML systems and Generative AI applications in a dynamic and impactful environment.

Responsibilities:

Design, Build, and Deploy Scalable ML Models

You will be responsible for end-to-end development of machine learning and deep learning models that can be scaled to handle real-world data and use cases. This includes training, testing, validating, and deploying models efficiently in production environments.

Develop NLP-Based Automation Solutions

You'll create natural language processing pipelines that automate tasks such as document understanding, text classification, and summarisation, enabling intelligent handling of property-related documents.

Prototype and Implement Generative AI Tools

Work closely with AI researchers and developers to experiment with and implement Generative AI techniques for tasks like content generation, intelligent suggestions, and workflow automation.

Integrate ML Models with APIs and Tools

Integrate machine learning models with external APIs and internal systems to support business operations and enhance customer service workflows.

Maintain CI/CD for ML Features

Collaborate with DevOps teams to manage CI/CD pipelines that automate testing, validation, and deployment of ML features and updates.

Review, Debug, and Optimise Models

Participate in thorough code reviews and model debugging sessions. Continuously monitor and fine-tune deployed models to improve their performance and reliability.

Cross-Team Communication

Communicate technical concepts effectively across teams, translating complex ML ideas into actionable business value.

·      Design, build, and deploy scalable ML and deep learning models for real-world applications.

·      Develop NLP-based and Gen AI based solutions for automating document understanding, classification, and summarisation.

·      Collaborate with AI researchers and developers to prototype and implement Generative AI tools.

·      Integrate ML and Gen AI models with APIs and internal tools to support business operations.

·      Work with CI/CD pipelines to ensure continuous delivery of ML features and updates.

·      Participate in code reviews, debugging, and performance optimisation of deployed models.

·      Communicate technical concepts effectively across cross-functional teams.

Essentials From Day 1:

Security and Compliance:

         • Ensure ML systems are built with GDPR compliance in mind.

         • Adhere to RBAC policies and maintain secure handling of personal and property         data.

Sandboxing and Risk Management:

         • Use sandboxed environments for testing new ML features.

         • Conduct basic risk analysis for model performance and data bias.

         • Use sandboxed environments for testing and development.

         • Evaluate and mitigate potential risks in model behavior and data pipelines

Qualifications:

·      1–2 years of professional experience in Machine Learning and Deep Learning projects.

·      Proficient in Python, Object-Oriented Programming (OOPs), and Data Structures & Algorithms (DSA).

·      Strong understanding of NLP and its real-world applications.

·      Exposure to building scalable ML systems and deploying models into production.

·      Basic working knowledge of Generative AI techniques and frameworks.

·      Familiarity with CI/CD tools and experience with API-based integration.

·      Excellent analytical thinking and debugging capabilities.

·      Strong interpersonal and communication skills for effective team collaboration.

• Relevant experience in React JS  5+ Year

• Experience in Hooks, Typescript

• Experience in GraphQL (Query & Mutations)
• Strong experience in Jest for Unit Testing
• Knowledge on docker, K8 and Kafka

1. Experience in working with both manual and tag management analytics implantations and common troubleshooting tools, including Developer Tools, Tag Assistant, or GA Debug
2. Experience with analytics strategies across multiple sites and apps, diverse platforms, and high-traffic sites preferred.
3. Knowledge of general Web best practices in SEM, SEO, and UX
4. Knowledge of Web markup and front-end Web development in HTML5, CSS3, or JavaScript
5. Ability to communicate with developers in a meaningful way.
6. Have the technical and communication skills to clearly communicate the processes and tasks to make full use of tag management and tags.

What you need to have:

• Graduate/ PG from Tier-1 colleges (preferably MBA in Sales and Marketing) 
• Minimum 3 years of experience in E– Commerce Marketing
• Deep understanding of Product Manager for a D2C or at an ecommerce marketplace
• Ability to structure and process qualitative or quantitative data and draw conclusions from it
• A probing mind    

• Manage sales operations in assigned district to achieve revenue goals.
• Supervise sales team members; the BSMs, on daily basis and provide guidance whenever needed.
• Identify skill gaps and conduct trainings to sales team.
• Work with team to implement new sales techniques to obtain profits.
• Assist in employee recruitment, promotion, retention and termination activities.
• Conduct employee performance evaluation and provide feedback for improvements.
• Contact potential customers and identify new business opportunities.
• Stay abreast with customer needs, market trends and competitors.
• Maintain clear and complete sales reports for management review.
• Build strong relationships with customers for business growth.
• Analyze sales performances and recommend improvements.
• Ensure that sales team follows company policies and procedures at all times.
• Develop promotional programs to increase sales and revenue.
• Plan and coordinate sales activities for assigned projects.