(d) Senior Machine Learning Engineer ic3

DEPOP; London; Hybrid; GBP 70,000 - 110,000; Full time

Job summary

A leading company in e-commerce seeks a Senior Machine Learning Engineer to enhance user experience through advanced ranking models. You will work within a dynamic team, leveraging cutting-edge technologies to optimize our platform's performance, while fostering a culture of innovation and collaboration.

Benefits

PMI and Bupa healthcare

25 days annual leave (+5 carryover)

Quarterly company-wide days off

Flexible working options

18 weeks paid parental leave

Conference budgets and subscriptions

Life insurance (3x salary)

Qualifications

• Proven experience in building ML pipelines and contributing to ML platforms.
• Solid understanding of systems design in cloud environments.
• Excellent communication for engaging stakeholders.

Responsibilities

• Design and implement ML pipelines for real-time models.
• Collaborate with ML Scientists and Backend Engineers.
• Maintain operational excellence with testing and monitoring.

Skills

Machine Learning Pipelines

Data Science Workflows

Systems Design

Excellent Communication

Ownership and Autonomy

Tools

Python

SageMaker

Databricks

PyTorch

TensorFlow

Spark

AWS

Kafka

Job description

Job Description

Role

At Depop, machine learning is integral to our value proposition.

In the ranking team, we build learning-to-rank models that power personalised experiences across the Depop app (in search results, recommendations, etc.).

The team currently consists of 3 Machine Learning Scientists and 1 Machine Learning Engineer. It owns models deployed in SageMaker for real-time inference, called upon by various services across the app (e.g., search service to rank results from our vector database in OpenSearch), serving millions of personalised results daily.

We are seeking a talented Senior Machine Learning Engineer to join our Ranking team.

As part of this team, you will participate in building, deploying, and monitoring future ranking models to enhance user experience across the app.

Responsibilities

• Design and implement pipelines for training, deploying, and monitoring real-time ranking models, collaborating with other ML Engineers.
• Work closely with ML Scientists on experimentation and deployment of new models.
• Collaborate with Backend Engineers (e.g., search service) to define requirements and plan experiments.
• Help design and build the ML platform at Depop alongside the MLOps infrastructure team, focusing on:
• Robust model prototyping and training
• CI/CD pipelines for deployment
• Model serving for real-time and batch processing
• Enhancing feature store for offline/online features
• Monitoring and alerting
• Maintain high standards for operational excellence, including service management, testing, monitoring, and issue resolution.
• Contribute to a strong engineering culture focused on innovation and professional growth.

Requirements

• Proven experience in building ML pipelines for training and deployment, and contributing to ML platforms.
• Knowledge of core data science and ML workflows.
• Strong ownership, autonomy, and organizational skills.
• Excellent communication skills for stakeholder engagement.
• Solid understanding of systems design in cloud environments (AWS, GCP).

Technologies and Tools

• Python
• ML/MLOps tools: SageMaker, Databricks, TFServing, etc.
• ML libraries: scikit-learn, PyTorch/TensorFlow, MLflow, etc.
• Spark & DataBricks
• AWS services: IAM, S3, Redis, ECS, etc.
• Shell scripting and related tools
• Experience with CI/CD practices
• Experience with streaming/batch systems (Kafka, Airflow, RMQ, etc.)

Additional Information

• Health & Wellbeing: PMI, Bupa healthcare, counselling, cycle-to-work, EAP, mental health support, etc.
• Work/Life Balance: 25 days annual leave (+5 carryover), quarterly company-wide days off, impact hours for volunteering, sabbatical after 5 years.
• Flexible Working: Hybrid model with options for Flex, Office, and Remote work (role-dependent); dog-friendly offices; work abroad for 4 weeks/year in UK tax treaty countries.
• Family Life: 18 weeks paid parental leave, IVF and shared parental leave, emergency parent/carer leave.
• Learn & Grow: Conference budgets, subscriptions, mentorship programs.
• Your Future: Life insurance (3x salary), pension matching up to 6%.
• Depop Extras: Free UK shipping on Depop sales, milestone rewards.