Lead/Senior Machine Learning Engineer
Location: New York City (Onsite - 4-5 days per week)
Industry: AdTech
Salary: $300K+ base + bonus/equity (higher flexibility for exceptional candidates)
Relocation Package offered
Overview of Role
- A leading Native Search advertising marketplace is hiring Lead and Senior Machine Learning Engineers to develop and optimize advanced models across its high-throughput ad-serving and consumer search platforms.
- This is a true end-to-end ML Engineering position. You'll own the full lifecycle, from data acquisition and model development through deployment, monitoring and ongoing optimization with no handoff to a separate engineering or MLOps team.
- The ideal candidate combines strong ML fundamentals with software-engineering depth and experience operating models in production. This is not a research-only Data Science or pure MLOps role.
Job Responsibilities
- End-to-End ML Ownership: Lead projects from data acquisition and prototyping through model development, production deployment, monitoring and optimization.
- Ranking & Search: Build models across Learning to Rank, relevance, recommendations, personalization, ad selection, bidding and yield optimization.
- Production Engineering: Develop scalable feature pipelines and online ML services designed for high throughput and low latency.
- ML Architecture: Make system and model architecture decisions across training, serving, validation, monitoring and ongoing performance.
- Experimentation: Design and run A/B tests and online experiments to evaluate models, features and measurable business impact.
- Technical Leadership: Partner across Product and Engineering, translate research into production systems, and mentor more junior ML Engineers.
Job Requirements
- Production ML: hands-on experience building, deploying and maintaining ML systems in production, depending on level.
- Education: Strong Computer Science degree/background, with solid software-engineering and ML fundamentals.
- Programming: Strong Python and SQL, with experience using PyTorch or TensorFlow and libraries such as scikit-learn.
- Infrastructure: Experience with Databricks/Spark, AWS, Docker and Kubernetes in distributed production environments.
- Relevant Domains: Learning to Rank is particularly valuable, alongside search, ranking, recommendations, personalization, retail, e-commerce or marketplace ML.
- System Design: Ability to design scalable ML services, explain architectural decisions and apply strong software-engineering practices.
- Leadership: Comfortable collaborating cross-functionally and supporting junior engineers; Lead candidates should demonstrate stronger architecture, mentorship and technical ownership.
- Industry: Direct AdTech experience is must for the Lead, but not required where the candidate has relevant production ML depth (flexibility here)
What the hiring team is really looking for:
- Less: Research-only Data Science, academic ML, pure MLOps, or Software Engineering with limited model-development experience.
- More: End-to-end production ML + software-engineering depth + ranking/search experience + system design + deployment and monitoring + technical mentorship.
Desired Skills and Experience
machine learning engineering, software engineering, ranking, search, personalization, aws, pytorch, pyspark, databricks, recommendation, docker, kubernetes
Sphere Digital Recruitment currently have a variety of job opportunities across digital so feel free to get in touch with us to find out how we can help you. Please take a look at our website.
Sphere is an equal opportunities employer. We encourage applications regardless of ethnic origin, race, religious beliefs, age, disability, gender or sexual orientation, and any other protected status as required by applicable law.
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