Senior Data Engineer / Lead Machine Learning Engineer

Company Description

Linkby is a global VC-funded adtech startup that helps D2C brands and publishers drive performance based cost-per-click revenue by harnessing trusted, quality content. Our solutions help make brands famous and allow publishers to better monetise the billions of moments of trust they create with their audiences.

Founded in Australia, Linkby now operates out of Sydney, London, New York, Toronto, Vancouver and more, and are proud proponents of a fully remote culture.

Position Overview

We are seeking an experienced Lead Data Engineer or Lead Machine Learning Engineer to drive the design, deployment, and optimization of large-scale recommender systems and machine learning models. The ideal candidate will have hands-on expertise in building robust data pipelines, deploying ML solutions into production, and optionally, experience with Databricks or similar platforms. You will play a key senior role in architecting data and ML infrastructure that powers personalized and predictive experiences for our users

Key Responsibilities

Lead the end-to-end deployment of recommender systems and machine learning models, ensuring scalability, reliability, and performance.

• Architect, build, and maintain efficient data pipelines and ETL processes to support ML workflows, including batch and real-time data processing.
• Collaborate with data scientists, engineers, and product teams to translate business requirements into technical solutions and deliver impactful recommendations.
• Oversee the integration of ML models into production environments, including monitoring, retraining, and model lifecycle management.
• Mentor and guide other engineers, fostering technical excellence and best practices in data engineering and ML deployment.
• Ensure data quality, governance, and compliance across all stages of the data and ML pipeline.
• Optimize and troubleshoot data workflows and ML serving infrastructure for maximum efficiency and reliability.
• (Optional) Leverage Databricks and related technologies (e.g., Spark, Delta Lake) to accelerate data processing and enable advanced analytics.
• Stay up to date with advancements in recommender systems, ML engineering, and big data technologies, applying new techniques as appropriate.

Qualifications & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• 6+ years of experience in data engineering, machine learning engineering, or related roles, with a proven track record of deploying ML models and recommender systems in production.
• Advanced proficiency in Python, SQL, and distributed data processing frameworks (e.g., Spark, Kafka).
• Strong experience with cloud platforms (AWS, Azure, GCP) and container orchestration (Docker, Kubernetes).
• Deep understanding of data architecture, ETL/ELT pipelines, and best practices for data quality and governance.
• Experience with MLOps tools and practices, including CI/CD, version control, and model monitoring.
• Excellent communication and leadership skills, with the ability to collaborate across technical and non-technical teams.

Preferred Skills & Experience

• Hands-on experience with Databricks, Delta Lake, and related big data technologies.
• Familiarity with real-time data streaming, event-driven architectures, and data lakehouse patterns.
• Exposure to machine learning pipelines, feature engineering, and model serving frameworks (MLflow, TensorFlow Serving, TorchServe).
• Knowledge of data security, privacy, and compliance standards.
• Experience leading agile teams and managing cross-functional projects.

We Offer

• Competitive salary and benefits package with equity options.
• Flexible working environment & hours - this role is 100% remote, and all employees are given access to WeWork as an option and we have regular team get-togethers!
• A dynamic and supportive work environment that fosters growth and development.
• Opportunities to work on cutting-edge technologies and projects that have high traffic and global impact.
• We are an equal opportunity employer and value diversity at our company.

No recruiters please.