ML Engineer - Personalization & Recommendation Systems Job at Krea (San Francisco)

Sr Staff ML Engineer - Applied AI

We are building AI-native discovery experiences across Mobility and Delivery. Se...

Location

United States , San Francisco

Salary:

267000.00 - 297000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Masters degree or Ph.D in Computer Science, Engineering, Mathematics
12+ years of ML experience, including significant work on large-scale deep learning systems
Demonstrated ownership of high-impact ML systems in search, recommendations, or conversational AI
Deep expertise in transformers, retrieval systems, ranking, and embedding architectures
Strong experience with PyTorch and distributed training
Proven ability to set the technical strategy for a large organization and influence product roadmaps at the executive level
Strong product intuition and ability to connect model improvements to business outcomes

Job Responsibility

Define and champion the multi-year technical vision and architecture for foundation models across Search, Recommendations, and Conversational AI
Set the architectural standard and drive system design for critical, high-leverage ML platforms across Mobility and Delivery
Lead cross-team initiatives spanning Retrieval, Ranking, Personalization, and LLM-powered assistants, resolving complex technical trade-offs across organizational boundaries
Define long-term investment areas (build vs fine-tune vs partner models) with clear business rationale and long-term viability
Provide principal-level technical leadership, mentoring Staff and Senior Staff engineers, and setting the bar for technical excellence across the entire AI organization

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
All full-time employees are eligible to participate in a 401(k) plan
Eligible for various benefits

Fulltime

Software Engineer II - Personalization (Growth & Marketing)

The Growth & Marketing organization sits at the intersection of infrastructure, ...

Location

United States , Seattle

Salary:

171000.00 - 190000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

3+ years of experience in backend or platform software engineering
Proficiency in at least one modern backend language (e.g., Go, Java)
Strong grasp of computer science fundamentals (data structures, algorithms, OOP)
Bachelor's degree in Computer Science, Engineering, or equivalent practical experience

Job Responsibility

Design, build, and operate scalable backend services for large-scale recommendation systems, including candidate generation, real-time content ranking and guardrailing
Partner with Applied Scientists to productionize and iterate on ML models that improve the relevance and quality of personalized content for millions of users
Collaborate closely with Product and Marketing teams to ship features that have a direct impact on user engagement and business growth
Write clean, maintainable code and participate in design reviews, code reviews, and incident responses

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
All full-time employees are eligible to participate in a 401(k) plan
Eligible for various benefits

Fulltime

Applied Scientist - Personalization and Recommendation

As an Applied Scientist at OnePay, you’ll be at the forefront of our AI and Mach...

Location

United States

Salary:

180000.00 - 220000.00 USD / Year

OnePay

Expiration Date

Until further notice

Requirements

Hands-on expertise with 2 years of experience building and productionizing ML/AI models that deliver measurable business impact
Experience building and productionizing LLM-powered applications, agentic systems, and traditional ML (ranking, recommendations, personalization)
A strong technical background with a degree in Computer Science, Data Science, Applied Mathematics, or a related field
Fluency in collaborating with Product, Engineering, and Analytics teams to bring AI solutions from ideation to deployment
Drive and proactivity – everyone here is a builder and executor

Job Responsibility

Design and deploy machine learning, deep learning, and LLM models that will shape our customer experience, drive business growth, and improve operational efficiency while collaborating closely with product, engineering, and analytics teams
Build intelligent AI agents that can reason, plan, and interact across workflows to enhance automation and decision-making
Develop personalization and recommendation systems that deliver dynamic, user-centric experiences across our product offerings
Design and optimize search and retrieval systems to improve discoverability, relevance, and user satisfaction

What we offer

Competitive base salary, stock options, and health benefits from Day 1
401(k) plan with company match
Remote-friendly (US), flexible time off (FTO), and opportunities for growth
A high-growth, mission-driven, inclusive culture where your work has real impact

Fulltime

Ai Engineer, Applied Ml

Perplexity is looking for an Applied ML Engineer to design, build, and iterate o...

Location

United States , San Francisco; New York City; Palo Alto

Salary:

210000.00 - 385000.00 USD / Year

Perplexity

Expiration Date

Until further notice

Requirements

5+ years experience building and shipping robust ML/AI models for large-scale, user-facing or data-driven products
Deep expertise in deep learning (PyTorch, TensorFlow, JAX), LLMs, information retrieval, content summarization, recommendation systems, NLP, and/or ranking
Strong software engineering skills (Python, production-quality codebases, collaborative development)
In-depth experience with the full ML lifecycle: data analysis, feature engineering, iterative model development, rigorous evaluation, and ongoing monitoring/improvement
Proven collaborator and communicator
excels in high-velocity, cross-functional teams
Curious, driven by end-user/product impact, and passionate about advancing the state of applied ML and AI
BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent experience)

Job Responsibility

Apply state-of-the-art ML and LLM techniques to solve problems spanning: Personalization (LLM memory, context summarization, retrieval and ranking)
Query Understanding (intent modeling, rewriting, agentic decomposition)
Content Discovery (feed ranking and surfacing)
Rigorously evaluate LLM/ML models with both offline and online techniques, designing experiments and metrics that provide deep insight into quality and impact
Own the entire model lifecycle from research to production: data analysis, modeling, evaluation, offline/online A/B testing, and iterative improvement
Collaborate cross-functionally with engineers, PMs, data scientists, and designers to ensure our AI drives meaningful product improvements
Stay at the forefront of ML/AI innovation by evaluating and incorporating emerging research and algorithms into the product lifecycle

What we offer

equity
health
dental
vision
retirement
fitness
commuter and dependent care accounts

Fulltime

Recommendation System Engineer

We are seeking a Machine Learning Engineer specializing in recommendation system...

Location

China , Shanghai

Salary:

Not provided

Meshy LLC

Expiration Date

Until further notice

Requirements

3+ years of professional experience in machine learning or recommendation systems
Strong coding skills in one or more languages: Python, Java, or Scala
Solid understanding of machine learning fundamentals, especially in ranking, collaborative filtering, and personalization
Hands-on experience with data processing frameworks (e.g., Spark, Flink) and ML libraries
Strong problem-solving and communication skills

Job Responsibility

Design, implement, and optimize recommendation and ranking algorithms
Analyze user behavior data to improve personalization and engagement
Evaluate and experiment with new ML methods to enhance recommendation quality

Fulltime

Staff Applied Machine Learning Engineer - Intelligent Data, Signals & Systems

As a Staff Applied Machine Learning Engineer focused on Intelligent Data, Signal...

Location

United States , Bay Area

Salary:

276800.00 - 415200.00 USD / Year

Cash App

Expiration Date

Until further notice

Requirements

12+ years building and operating production software and ML systems for business-critical products
Deep expertise in intelligent systems such as ranking/retrieval, recommendations, search, personalization, growth and lifecycle ML, customer intelligence, propensity/churn/LTV, next-best-action, or model-derived risk signals
Strong production ML judgment across feature pipelines, model serving, experimentation, monitoring, feedback loops, online/offline consistency, and reliable signal interfaces
Ability to evaluate impact beyond short-term conversion, including trust, fairness, access, risk, compliance, and long-term engagement
Experience using AI-assisted engineering tools with appropriate verification, testing, and review for customer-impacting systems.

Job Responsibility

Build and operate production ML systems that turn customer and product context into trusted signals, rankings, recommendations, and decision capabilities
Design production data and signal contracts that define intended use, freshness, provenance, confidence, eligibility, and calibration for downstream consumers
Own ranking, retrieval, recommendation, search, propensity, and next-best-action systems end to end, from feature and candidate generation through serving, experimentation, monitoring, and feedback loops
Evaluate customer and business impact beyond short-term conversion, including trust, fairness, access, risk, compliance, long-term engagement, and segment-level performance
Partner across product, growth, data, platform, modeling, risk, and compliance to translate ambiguous goals into measurable ML system designs
Use AI and agents to accelerate development, analysis, testing, documentation, and operations while exposing reusable capabilities to product services, internal tools, and AI-assisted workflows.

What we offer

Remote work
Medical insurance
Flexible time off
Retirement savings plans
Modern family planning

Fulltime

Technical Architect - Business Applications

Roku is changing how the world watches TV. Roku is the #1 TV streaming platform ...

Location

United States , Boston

Salary:

250000.00 - 450000.00 USD / Year

Roku

Expiration Date

Until further notice

Requirements

Master's or PhD in Computer Science, Mathematics, Statistics, or a related technical field, or equivalent practical experience.
10+ years of hands-on engineering experience, with a track record of technically leading and delivering large-scale assistant or autonomous systems
Strong foundation in machine learning and statistical modeling, including clustering, classification, regression, decision trees, neural networks, SVMs, and anomaly detection, with deep understanding of supervised and unsupervised learning, feature engineering, model evaluation, bias-variance tradeoffs, and offline vs. online metrics.
Proven experience building and scaling production ML and AI systems, including LLMs, RAG architectures, embeddings, retrieval-based systems, and multi-agent or agent-based system design.
Hands-on experience designing, training, tuning, and deploying models for ranking, prediction, recommendation, forecasting, classification, or NLP use cases.
Experience with cloud platforms (AWS, Azure, Google Cloud), microservices, containerization (Docker, Kubernetes), and DevOps
Demonstrated technical leadership, including setting direction, influencing across teams, and elevating the work of other engineers.
Experience in advertising, marketplaces, e-commerce, travel, or similar data-rich, decision-driven platforms is a strong plus.

Job Responsibility

Develop and oversee technical strategy for Roku's platform that support diverse business applications.
Drive the AI-native transformation of Roku's advertising business operations, identifying high-leverage opportunities and influencing roadmap, architecture, and system design across multiple teams.
Start from the needs of internal engineers and business operators, bringing a creative and strategic approach to simplifying systems and introducing practical, high-impact solutions.
Work closely with advertising business stakeholders to identify needs, surface high-impact opportunities, and translate operational pain points into ML and agentic AI solutions.
Design and ship production ML and agentic systems end-to-end, including recommendation, personalization, ranking, forecasting, anomaly detection, and multi-agent or agent-to-agent workflows, embedded directly within product and operational systems where they drive decisions.
Apply GenAI and LLMs to create measurable value, building and scaling Retrieval Augmented Generation (RAG) pipelines, prompt orchestration, evaluation frameworks, and guardrails, with a focus on reliability and outcomes over hype.
Translate ambiguous business problems into production solutions, partnering with engineers, data scientists, product managers, and business teams to ground ML and AI work in real operational impact.
Build and operationalize evaluation loops covering precision and recall, calibration, drift detection, and human-in-the-loop systems, and define the dashboards and Service Level Objectives (SLO) that tie model performance to business outcomes.
Provide technical leadership across the broader ML and AI surface area, raising the bar for engineering rigor, mentoring engineers, and shaping how the organization thinks about AI-native systems.

What we offer

Health insurance
Equity awards
Life insurance
Disability benefits
Parental leave
Wellness benefits
Paid time off
Global access to mental health and financial wellness support and resources
Local benefits including healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension)

Fulltime

Senior Applied Scientist

As a Senior Applied Scientist, you will build and ship the AI/ML that powers the...

Location

France , Paris

Salary:

Not provided

Bsport

Expiration Date

Until further notice

Requirements

4+ years of experience building and shipping machine learning in production, including models that reached a real product and moved meaningful metrics
You think of yourself as a builder first, writing production-grade code and taking responsibility for getting models live rather than leaving them in a notebook
Genuine depth in modern machine learning, recommendation and personalization systems, embeddings, and forecasting
Fluent in Python and worked hands-on on ML solutions
Track record of taking work developing solutions, from an open problem to a validated solution running in production
Communicates with clarity and moves comfortably between technical peers and product stakeholders

Job Responsibility

Take end-to-end ownership of product-facing models, from problem definition and experimentation through to a deployed and dependable solution
Develop the AI&ML capabilities users experience directly, spanning personalisation, recommendations, LLM-powered and generative features, embeddings, and forecasting
See your work through to production rather than handing it over, partnering with Engineering on questions of deployment, latency, cost, and ongoing monitoring
Establish a clear definition of success for each initiative, designing the metrics and evaluation that demonstrate genuine product impact
Contribute to the technical direction of applied AI&ML at bsport
Support the development of fellow scientists and engineers, leading through the example of the work you deliver

What we offer

Attractive compensation package
Competitive salary packages based on your experience and role
Hybrid model with 3 days per week in the office
Up to 15 days of remote work from abroad each year
Specially discounted HelloCSE membership
Multicultural colleagues, after-work events, team-building & more

Fulltime

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ML Engineer - Personalization & Recommendation Systems

Job Description

Job Responsibility

Requirements

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