Role at a glance
- Salary
- Not Disclosed
- Location
- Belgrade London
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- Minimum 5 years of relevant industry experience.
Spotted an issue?
We’ll check it against the original posting.
Role Summary
The Machine Learning Engineer improves search quality across the middle and later stages of ranking. The role owns ranking-quality problems end to end, from evaluation and bottleneck identification through solution development and safe deployment.
What You'll Do
- Improve search quality through models, data, evaluation, infrastructure, or other available leverage.
- Define evaluations, identify ranking bottlenecks, build solutions, and ship them safely.
- Train and evaluate retrieval, ranking, and classification models, including neural and LLM-based approaches where appropriate.
- Build and operate ranking infrastructure for feature computation, low-latency inference, multi-stage cascades, deployment, and monitoring.
- Balance quality, latency, reliability, cost, and engineering complexity.
- Collaborate across Data, AI, Infrastructure, and Product while owning the quality outcome.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Deep understanding of search or recommender systems and their evaluation; proven ownership of a large-scale production ranking system or substantial quality problems; strong machine-learning and software-engineering skills across data, models, serving, and monitoring; ability to drive ambiguous cross-team problems; exceptional depth in either modern neural ranking methods or low-latency ranking systems and runtime.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Perplexity is seeking an experienced Machine Learning Engineer to improve search quality across the middle and later stages of ranking. We are looking for a strong ranking generalist who can own ambiguous problems end to end and brings exceptional depth in either neural ranking or production ranking systems.
Responsibilities
Relentlessly push search quality forward through models, data, evaluation, infrastructure, or any other leverage available.
Own ranking-quality problems end to end: define the evaluation, identify the bottleneck, build the solution, and ship it safely.
Train and evaluate retrieval, ranking, and classification models, including neural and LLM-based approaches where appropriate.
Build and operate ranking infrastructure, including feature computation, low-latency inference, multi-stage cascades, deployment, and monitoring.
Make sound trade-offs across quality, latency, reliability, cost, and engineering complexity.
Collaborate across Data, AI, Infrastructure, and Product while retaining ownership of the final quality outcome.
Qualifications
Deep understanding of search or recommender systems and their evaluation.
Proven ownership of a large-scale production ranking system or a substantial class of quality problems.
Strong machine-learning and software-engineering skills across data, models, serving, and monitoring.
Ability to drive ambiguous, cross-team problems without continuous task decomposition.
Exceptional depth in either modern neural ranking methods or low-latency ranking systems and runtime.
Minimum 5 years of relevant industry experience.
About the company
Perplexity
Startup
Perplexity is an innovative technology company that specializes in developing advanced artificial intelligence solutions aimed at enhancing human-computer interaction. With a focus on natural language processing and machine learning, Perplexity empowers users to access information and insights more intuitively and efficiently. The company is dedicated to creating tools that simplify complex data and foster informed decision-making, thereby transforming the way individuals and organizations engage with knowledge. Through its commitment to excellence and user-centric design, Perplexity is shaping the future of information retrieval and analysis.