Lead Machine Learning Engineer

adMarketplace; York and North Yorkshire; On-site; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Medical/Dental/Vision/FSA

Wellness Programs & Social Events

Life/Disability Insurance

Matching 401k

Employee Referral Bonus Program

Discounted Gym Membership

Tax-Free Commuter Benefits

Job summary

adMarketplace in York, UK is seeking a Lead Machine Learning Engineer to own end-to-end ML projects in our ultra-low-latency ad-serving platform and search solutions.

You will drive model development, deployment, and optimization, champion MLOps, mentor juniors, and collaborate with product and engineering to improve relevancy, yield, and bidding performance in a fast-paced environment.

Qualifications

• 2+ years of experience in building AI/ML models in at least one of the following domains: Ads, relevance, ranking, recommendation systems, and search
• PhD with 5+ years of experience or MS with 5-8+ years of industry experience in AI/ML, developing and deploying production-grade ML systems
• 3+ years of experience in deploying and maintaining ML pipelines in production, including feature engineering and model monitoring frameworks
• 2+ years of experience in Python and proficiency with distributed frameworks (Spark, Hadoop), SQL, and cloud infrastructure
• 2+ years of experience with ML packages such as Tensorflow or PyTorch, scikit-learn, and Spark ML
• 3+ years of experience in building distributed, low-latency, high-throughput batch and online ML services
• 5+ years of experience in building ML models for ads, search and/or recommender systems including CTR/CVR prediction, ad selection, keyword bidding, and Learning to Rank models
• 2+ years of experience in building and deploying online experimentation frameworks to identify right models and features at scale
• 2+ years of experience in building ad selection frameworks using reinforcement learning or contextual bandits
• Experience in fine tuning LLMs
• 1+ years of experience in building products using Generative AI powered autonomous agents

Responsibilities

• Drive end-to-end lifecycle management of AI/ML projects from concept and data acquisition to prototyping, model development, deployment, optimization and ongoing maintenance
• Implement and champion best practices in MLOps, including data collection, model training pipelines, model deployments, monitoring, alerting, and QA to ensure model reliability and performance
• Contribute significantly to model architecture decisions, leveraging state-of-the-art machine learning, deep learning, and reinforcement learning techniques
• Develop and deploy robust feature engineering pipelines and ML services optimized for low latency and high throughput
• Establish and utilize robust A/B testing and experimentation frameworks to evaluate and iteratively improve model performance
• Translate research papers into high-quality, production-ready code
• Communicate effectively, collaborate, and build long-term relationships across the organization
• Mentor junior team members in achieving engineering excellence and be a change agent on the team

Skills

AI/ML model development

Low-latency systems

MLOps

A/B testing

Reinforcement learning

Generative AI

Mentoring

Communication

Education

PhD in AI/ML or related field

MS in AI/ML or related field

Tools

Python

Spark

Hadoop

TensorFlow

PyTorch

Spark ML

Job description

• We are seeking an experienced Lead Machine Learning Engineer passionate about building impactful products in the search and advertising technology ecosystem
• As part of our established AI/ML and Search organization, you will be instrumental in developing and optimizing advanced models and applications to enhance our ultra-low-latency ad-serving platform and consumer-facing search solutions
• You will collaborate closely with product, business, and other engineering teams, making significant contributions to strategic initiatives such as relevancy & yield optimization, predictive modeling, and improved bidding performance
• You will have a clear career progression path and numerous opportunities for both personal and professional growth in an intellectually stimulating and dynamic work environment
• Drive end-to-end lifecycle management of AI/ML projects from concept and data acquisition to prototyping, model development, deployment, optimization and ongoing maintenance
• Implement and champion best practices in MLOps, including data collection, model training pipelines, model deployments, monitoring, alerting, and QA to ensure model reliability and performance
• Contribute significantly to model architecture decisions, leveraging state-of-the-art machine learning, deep learning, and reinforcement learning techniques
• Develop and deploy robust feature engineering pipelines and ML services optimized for low latency and high throughput
• Establish and utilize robust A/B testing and experimentation frameworks to evaluate and iteratively improve model performance
• Translate research papers into high-quality, production-ready code
• Communicate effectively, collaborate, and build long-term relationships across the organization
• Mentor junior team members in achieving engineering excellence and be a change agent on the team

Benefits

• Medical/Dental/Vision/FSA
• Wellness Programs & Social Events
• Life/Disability Insurance
• Matching 401k
• Employee Referral Bonus Program
• Discounted Gym Membership
• Tax-Free Commuter Benefits

2+ years of experience in building AI/ML models in at least one of the following domains: Ads, relevance, ranking, recommendation systems, and searchPhD with 5+ years of experience or MS with 5-8+ years of industry experience in AI/ML, developing and deploying production-grade ML systems3+ years of experience in deploying and maintaining ML pipelines in production, including feature engineering and model monitoring frameworks2+ years of experience in Python and proficiency with distributed frameworks (Spark, Hadoop), SQL, and cloud infrastructureAbility to operate efficiently in a high-paced, multi-functional, and rapidly evolving environment2+ years of experience with ML packages such as Tensorflow or PyTorch, scikit-learn, and Spark ML3+ years of experience in building distributed, low-latency, high-throughput batch and online ML services5+ years of experience in building ML models for ads, search and/or recommender systems including CTR/CVR prediction, ad selection, keyword bidding, and Learning to Rank models2+ years of experience in building and deploying online experimentation frameworks to identify right models and features at scale2+ years of experience in building ad selection frameworks using reinforcement learning or contextual banditsExperience in fine tuning LLMs1+ years of experience in building products using Generative AI powered autonomous agents