Staff Machine Learning Engineer Search Ranking

Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves live in the moment learn about the world and have fun together. The Company’s three core products are Snapchat a visual messaging app that enhances your relationships with friends family and the world; Lens Studio an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses Spectacles.

Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world every day. We’re deeply committed to the well-being of everyone in our global community which is why our values are at the root of everything we do. We move fast with precision and always execute with privacy at the forefront.

​We’re looking for a Staff Machine Learning Engineer to join Snap Inc! We are looking for a Staff Machine Learning Engineer to lead the development of next-generation Search ranking systems. In this role you will design build and improve machine learning models that determine the relevance quality personalization and utility of search results at scale.

What You’ll Do

• Lead the design and development of machine learning models for Search ranking including relevance ranking personalization result quality intent understanding and engagement optimization

• Own major ranking initiatives from problem definition through experimentation launch and iteration

• Develop and improve ranking models using techniques such as learning-to-rank deep retrieval neural ranking sequence models embeddings multi-task learning calibrated prediction and large-scale feature engineering

• Build ranking systems that balance multiple objectives such as relevance user satisfaction freshness diversity fairness safety latency and business goals

• Partner with product managers data scientists and engineers to define success metrics experimentation strategy and long-term ranking roadmap

• Analyze user behavior search logs query-result interactions and model performance to identify opportunities for improvement

• Design robust offline evaluation online experimentation and model monitoring frameworks

• Improve feature pipelines training infrastructure serving systems and model iteration velocity

• Provide technical leadership across teams influence architecture decisions and mentor engineers working on ML ranking systems

• Stay current with advances in search recommendation systems ads ranking generative AI LLM-based ranking and retrieval-augmented systems

Knowledge Skills & Abilities

• Strong machine learning fundamentals including supervised learning ranking models embeddings deep learning optimization evaluation and experimentation

• Strong programming skills in Python C++ Java Scala or similar languages

• Experience with large-scale data processing and ML infrastructure such as Spark Flink Beam TensorFlow PyTorch JAX or similar tools

• Ability to take ML models from research or prototyping into large-scale production systems

• Strong understanding of online experimentation A/B testing metric design model debugging and tradeoff analysis

• Proven ability to lead complex technical projects across multiple teams

• Excellent communication skills and ability to explain complex ML concepts to technical and non-technical stakeholders

Minimum Qualifications

• Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience

• 8+ years of post-Bachelor’s machine learning experience; or Master’s degree in a technical field + 7+ year of post-grad machine learning experience; or PhD in a relevant technical field + 4 years of post-grad machine learning experience

• Experience developing machine learning models for relevance ranking personalization intent understanding and/or engagement optimization

• Experience with large-scale data processing and ML infrastructure such as Spark Flink Beam TensorFlow PyTorch JAX or similar tools

Preferred Qualifications

• Advanced degree in Computer Science Machine Learning Statistics Mathematics Information Retrieval or a related field

• Direct experience building Search ranking systems including query understanding retrieval ranking re-ranking relevance modeling or result blending

• Experience with ads ranking recommendation ranking feed ranking marketplace ranking or content discovery systems

• Experience with learning-to-rank methods such as LambdaMART pairwise/listwise ranking losses neural ranking models or transformer-based rankers

• Experience with candidate generation retrieval models ANN search embeddings vector search or two-stage ranking architectures

• Experience optimizing ranking systems for multiple objectives including relevance engagement quality diversity freshness long-term user value and monetization

• Experience with LLMs foundation models semantic search natural language understanding or retrieval-augmented generation

• Experience building low-latency ML serving systems and improving production model reliability

• Track record of publishing patenting or otherwise advancing the state of the art in search ranking recommendations ads or applied ML

If you have a disability or special need that requires accommodation please don’t be shy and provide us some information.

"Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster reinforce our values and serve our community customers and partners better through dynamic collaboration. To reflect this we practice a “default together” approach and expect our team members to work in an office 4+ days per week. 

At Snap we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer and committed to providing employment opportunities regardless of race religious creed color national origin ancestry physical disability mental disability medical condition genetic information marital status sex gender gender identity gender expression pregnancy childbirth and breastfeeding age sexual orientation military or veteran status or any other protected classification in accordance with applicable federal state and local laws. EOE including disability/vets.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring where applicable).

Our Benefits: Snap Inc. is its own community so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy on your own terms. Our benefits are built around your needs and include paid parental leave comprehensive medical coverage emotional and mental health support programs and compensation packages that let you share in Snap’s long-term success!

Compensation

In the United States work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills experience qualifications work location and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.

Zone A (CA WA NYC):

Zone B:

Zone C:

What We Do

We contribute to human progress by empowering people to express themselves live in the moment learn about the world and have fun together.

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