Member Of Technical Staff (Machine Learning Engineer, Ranking Quality - Search)
perplexity
Job Score
90 ptsPerplexity 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 Artificial Intelligence
Artificial Intelligence is currently the fastest-growing field in the technology market. The revolution in generative models (GPT, Claude, Gemini) has created massive demand for AI-specialized professionals.
Key areas of practice include Machine Learning Engineering, MLOps, Prompt Engineering, AI Research, and Applied AI. Python, TensorFlow, PyTorch, and LLM knowledge are essential skills.
AI salaries are the highest in the technology sector, with many remote work opportunities at international companies.
About Account Manager
The Account Manager is the professional responsible for managing and expanding the relationship with clients after the sale. They act as a strategic partner, ensuring satisfaction, retention, and account growth, connecting client needs with company solutions.
Key skills include relationship management, negotiation, upsell and cross-sell, contract renewal, account planning, business reviews, metrics analysis (NPS, churn, LTV), and CRM knowledge (Salesforce, HubSpot). Communication, empathy, and business vision are fundamental differentiators.
Account Managers in technology and SaaS companies are highly valued, especially those who can increase recurring revenue (MRR/ARR) through account expansion and churn prevention. The field offers opportunities from account executive to director of accounts, with a focus on strategic relationship, revenue growth, and customer success.
Discover Other Areas
Understand the scope of work, key skills, and tools used in different career areas.
About Data
The Data field has undergone a radical transformation with the rise of Generative AI. Data professionals are fundamental for evidence-based decision-making across all industries.
Key specializations include Data Engineering, Data Science, Business Intelligence, Machine Learning Engineering, and Analytics. Tools like SQL, Python, Spark, dbt, and cloud platforms (AWS, GCP, Azure) are essential.
The data market continues with high demand and salaries among the most competitive in the technology sector, with many remote work opportunities.
About Talent Acquisition
Talent Acquisition is the strategic area responsible for attracting, selecting, and hiring the best professionals for the organization. Unlike traditional recruitment, TA acts as a strategic business partner, aligning talent acquisition with the company's long-term objectives.
Key skills include advanced sourcing, employer branding, labor market analysis, talent pipeline management, and candidate experience. Tools like LinkedIn Recruiter, ATS (Greenhouse, Lever, Ashby), and assessment platforms are essential.
TA professionals in technology companies are highly valued, especially those who master tech sourcing, workforce planning, and recruitment metrics like time-to-hire and cost-per-hire.
About Traffic Manager
The Traffic Manager is the professional responsible for planning, executing, and optimizing paid media campaigns across various digital platforms. With the competitiveness of the digital market, paid traffic professionals are essential for generating qualified leads and maximizing return on advertising investment.
Key skills include campaign management on Google Ads, Meta Ads, LinkedIn Ads, and TikTok Ads, media planning, metrics analysis (ROAS, CPA, CPC, CTR), A/B testing, remarketing, and landing page creation. Tools like Google Analytics, Google Tag Manager, Hotjar, and automation platforms are essential.
Traffic managers in technology companies are highly valued, especially those who master performance marketing, conversion funnel optimization, and scaling strategies. The field offers opportunities from media analyst to head of performance, with a focus on growth, budget efficiency, and return on investment.
About Communications
The Communications area is strategic for building and maintaining a company's institutional image. It encompasses corporate, internal, and external communication, public relations, press office, and reputation management. Communications professionals are responsible for delivering consistent messages that strengthen the employer brand and market positioning.
Key skills include strategic writing, communication planning, crisis management, media relations, corporate content production, event organization, and digital communication. Knowledge of communication CRMs, press release distribution platforms, and media monitoring tools (Meltwater, Cision) is a differentiator.
Corporate communicators in technology companies are highly valued, especially those who master change communication, employee engagement, and digital communication. The field offers opportunities in startups, scale-ups, and large corporations, with a focus on storytelling, organizational culture, and innovation communication.
About Business Intelligence
Business Intelligence (BI) is the area responsible for transforming raw data into strategic information for decision-making. BI professionals build dashboards, reports, and analyses that help companies understand their performance and identify growth opportunities.
Key skills include data modeling (star schema, snowflake), ETL (extraction, transformation, loading), advanced SQL, BI tools (Power BI, Tableau, Looker), data warehousing, KPIs, and business metrics analysis (MRR, churn, cohort). Knowledge of dbt, Airflow, and data pipelines is a differentiator.
BI professionals in technology companies are highly valued, especially those who master data visualization, analytics engineering, and can translate complex data into actionable insights for the business. The field offers opportunities from BI analyst to head of data, with a focus on data-driven decision making.
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