At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.

We're the only company offering three integrated solutions for frontier AI development:

• Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale

• Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models

• Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling

Why Join Us

• High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions.

• Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence.

• Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution.

• Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI.

• Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics.

Role Overview

We’re looking for a Full-Stack AI Engineer to join our team, where you’ll build the next generation of tools for developing, evaluating, and training state-of-the-art AI systems. You will own features end to end,from user-facing experiences and APIs to backend services, data models, and infrastructure.

You’ll be at the heart of our applied AI efforts, with a particular focus on human-in-the-loop systems used to generate high-quality training data for Large Language Models (LLMs) and AI agents. This includes building a platform that enables us and our customers to create and evaluate data, as well as systems that leverage LLMs to assist with reviewing, scoring, and improving human submissions.

Your Impact

• Own End-to-End Product Features

Design, build, and ship complete workflows spanning frontend UI, APIs, backend services, databases, and production infrastructure.

• Enable Human-in-the-Loop AI Training

Build systems that allow humans to efficiently create, review, and curate high-quality training and evaluation data used in AI model development.

• Support RLHF and Preference Data Workflows

Design and implement tooling that supports RLHF-style pipelines, including task generation, human review, scoring, aggregation, and dataset versioning.

• Leverage LLMs in the Review Loop

Build systems that use LLMs to assist human reviewers,such as automated checks, critiques, ranking suggestions, or quality signals,while maintaining human oversight.

• Advance AI Evaluation

Design and implement evaluation frameworks and interactive tools for LLMs and AI agents across multiple data modalities (text, images, audio, video).

• Create Intuitive, Reviewer-Focused Interfaces

Build thoughtful, efficient user interfaces (e.g., in React) optimized for high-throughput human review, quality control, and operational workflows.

• Architect Scalable Data & Service Layers

Design APIs, backend services, and data schemas that support large-scale data creation, review, and iteration with strong guarantees around correctness and traceability.

• Solve Ambiguous, Real-World Problems

Translate loosely defined operational and research needs into practical, scalable, end-to-end systems.

• Ensure System Reliability

Participate in on-call rotations to monitor, troubleshoot, and resolve issues across the full stack.

• Elevate the Team

Improve engineering practices, development processes, and documentation. Share knowledge through technical writing and design discussions.

What You Bring

• Bachelor’s degree in Computer Science, Data Engineering, or a related field.

• 2+ years of experience in a software or machine learning engineering role.

• A proactive, product-focused mindset and a high degree of ownership, with a passion for building solutions that empower users.

• Experience using frontend frameworks like React/Redux and backend systems and technologies like Python, Java, GraphQL; familiarity with NodeJS and NestJS is a plus.

• Knowledge of designing and managing scalable database systems, including relational databases (e.g., PostgreSQL, MySQL), NoSQL stores (e.g., MongoDB, Cassandra), and cloud-native solutions (e.g., Google Spanner, AWS DynamoDB).

• Familiarity with cloud infrastructure like GCP (GCS, PubSub) and containerization (Kubernetes) is a plus.

• Excellent communication and collaboration skills.

• High proficiency in leveraging AI tools for daily development (e.g., Cursor, GitHub Copilot).

• Comfort and enthusiasm for working in a fast-paced, agile environment where rapid problem-solving is key.

Bonus Points

• Experience building tools for AI/ML applications, particularly for data annotation, monitoring, or agent evaluation.

• Familiarity with data infrastructure components such as data pipelines, streaming systems, and storage architectures (e.g., Cloud Buckets, Key-Value Stores).

• Previous experience with search engines (e.g., ElasticSearch).

• Experience in optimizing databases for performance (e.g., schema design, indexing, query tuning) and integrating them with broader data workflows.

Engineering at Labelbox

At Labelbox Engineering, we're building a comprehensive platform that powers the future of AI development. Our team combines deep technical expertise with a passion for innovation, working at the intersection of AI infrastructure, data systems, and user experience. We believe in pushing technical boundaries while maintaining high standards of code quality and system reliability. Our engineering culture emphasizes autonomous decision-making, rapid iteration, and collaborative problem-solving. We've cultivated an environment where engineers can take ownership of significant challenges, experiment with cutting-edge technologies, and see their solutions directly impact how leading AI labs and enterprises build the next generation of AI systems.

Our Technology Stack

Our engineering team works with a modern tech stack designed for scalability, performance, and developer efficiency:

• Frontend: React.js with Redux, TypeScript

• Backend: Node.js, TypeScript, Python, some Java & Kotlin

• APIs: GraphQL

• Cloud & Infrastructure: Google Cloud Platform (GCP), Kubernetes

• Databases: MySQL, Spanner, PostgreSQL

• Queueing / Streaming: Kafka, PubSub

Labelbox strives to ensure pay parity across the organization and discuss compensation transparently. The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.

Annual base salary range $130,000-$200,000 USD

Life at Labelbox

• Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland

• Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility

• Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making

XML job scraping automation by YubHub

Key responsibilities include:

• Design and building of tooling and automated processes for provisioning and execution of Elasticsearch performance benchmarking jobs at scale.
• Defining methodologies and guidelines for performance benchmarking servicing development teams and solution architects.
• Play a lead role in cross-functional team efforts and engagements.
• Mentoring and advising team members on proposed technical solutions.
• Developing reporting for and interpreting of benchmarking results.
• Investigate and assist in resolving performance escalations and capacity planning issues.
• Address and devise solutions for benchmarking disparate use cases and workloads.

Requirements include:

• Software development experience with Python and Linux shell required (Expert Level).
• Familiarity with Linux system-level performance measurement and associated tooling.
• Prior experience in the troubleshooting and root cause analysis of performance issues in complex distributed architectures.
• Prior experience with CI/CD pipelines and automating process workflows.
• Experience in cloud architectures, service models, and operating across multiple cloud service providers, assessing tradeoffs from both performance and deployment perspectives.
• Ability to multitask, effectively manage your time, and collaborate with team members globally across time zones.
• Familiarity with measuring performance and sizing in Linux VM and container environments.
• Experience with performance tuning of Java applications and JVMs.

Bonus points for prior experience with large, distributed search engines and in developing and tuning queries, familiarity with the Elasticsearch Query API and building Kibana dashboards, cloud orchestration with Kubernetes, and experience applying the use of Artificial Intelligence (AI) for devising and expanding benchmarking practices and enhancing benchmarking tooling.

XML job scraping automation by YubHub

Key responsibilities include:

• Design and building of tooling and automated processes for provisioning and execution of Elasticsearch performance benchmarking jobs at scale.

• Defining methodologies and guidelines for performance benchmarking servicing development teams and solution architects.

• Play a lead role in cross-functional team efforts and engagements.

• Mentoring and advising team members on proposed technical solutions.

• Developing reporting for and interpreting of benchmarking results.

• Investigate and assist in resolving performance escalations and capacity planning issues.

• Address and devise solutions for benchmarking disparate use cases and workloads.

This role requires software development experience with Python and Linux shell, familiarity with Linux system-level performance measurement and associated tooling, prior experience in the troubleshooting and root cause analysis of performance issues in complex distributed architectures, and experience in cloud architectures, service models, and operating across multiple cloud service providers.

In addition to cash compensation, this role is currently eligible to participate in Elastic's stock program and has a company-matched Registered Retirement Savings Plan (RRSP) with dollar-for-dollar matching up to 6% of eligible earnings.

XML job scraping automation by YubHub

As a Digital Analytics Consultant, you will follow an action plan, issuing various deliverables during the project. You will guarantee the quality of web analytics data as well as its interpretation during delivery sessions with the client. You will be responsible for the content, the format and the overall quality of the outputs delivered to the client and for monitoring their operational and technical implementation.

Based on your good understanding of our expertise and our clients' needs, you will collaborate with all of our teams to develop fifty-five's offer, both in terms of marketing and in terms of technical and operational delivery.

Job description

• Deliver missions related to the monitoring of the client's digital activity based on key performance indicators (reporting), to onsite conversion optimization through data analysis and web & app testing, data visualization and related inquiries.
• Analyse data and structure relevant information for the client's benefit, in line with business indicators specific to their industry (eg. mobile operators, retail, travel, etc.)
• Meet clients' needs and pay attention to the quality of all deliverables

Education and Experience

• Master's degree (business, engineering) or equivalent diploma
• Fluent in Chinese (Cantonese) and English written and spoken
• 0-2 years (Consultant) / 3-5 years (senior Consultant) experience in project management or digital marketing, or media-buy agencies, digital or traditional, or consulting firms (strategy, organization, change management, IS, etc.), business Intelligence software publishers (SAP, etc.)
• Good to have knowledge of the main online acquisition channels: search engines (SEO, SEM and bid-management tools), display, affiliate marketing, emailing, social media, AdExchange, web and mobile applications, etc.
• Experience in Adobe Analytics and/or Adobe Target is an advantage
• Industry web & app analytics tool
• Data Visualization / Business Intelligence Tools
• Good to have SQL and Python for data analysis
• Strong analytical skills
• Good social spirit
• Laid back but professional
• Curious and willing to learn (a lot!)
• Strong interest in new technologies and the digital industry

Benefits

• 20 days Annual Leaves
• Extra medical coverage, including inpatient and outpatient
• Work remotely (Maximum 2 days a week Work From Home policy)
• Regular team activities including TGIF, team lunch and Off-site!
• A multicultural environment with employees from over 20 countries
• Values centred on excellence, caring and sharing
• Continuous (and certified) training on the digital ecosystem and technologies (initial training for all new employees, followed by ongoing training sessions, etc.)
• Particular importance given to work-life balance and the right to disconnect

The opportunity of taking part in internal projects such as The Data Hive (a “tech for good” project initiated by fifty-fivers, whose aim is to put knowledge and expertise at the disposal of charitable organisations) or Women@55 (a committee with the aim of discussing gender equality and the role of women in consulting, Tech and at fifty-five)

fifty-five encourages diversity and is committed to guaranteeing equal treatment of all applications, regardless of gender, age, origin, sexual orientation, state of health or political or religious opinion.

XML job scraping automation by YubHub

Hundreds of millions of users visit Bing.com worldwide monthly, and we have a large opportunity to grow further. At Bing, we celebrate our data-driven culture: changes only ship when their impact is understood and positive. This role is a great opportunity to make solid, and even multiplicative impact on the org.

As a data and applied scientist in this team, you will have the chance to work on and deliver metrics that drive the direction of major Bing initiatives. You will have the chance to be involved in the analysis and decision making for 1000s of online controlled A/B experiments.

Microsoft’s mission is to empower every person and every organisation on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realise our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Responsibilities:

• Design, analyse, and interpret A/B online experiments to evaluate user engagement and generate actionable, trustworthy insights that inform product decisions.
• Perform hands-on analysis of large-scale telemetry data using advanced statistical methods, algorithms, and data tools to uncover meaningful patterns and trends.
• Develop and monitor key success metrics to measure and improve Bing customer satisfaction, engagement, and retention.
• Formulate data-driven strategies to understand correlations among critical Bing metrics and deliver clear, rigorous ship decisions.
• Effectively communicate analytical methodologies, data visualisations, and evidence-based recommendations across cross-functional teams to drive alignment and impact.

Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.

Preferred Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.

Experience with SQL-like query languages. Hands on experience in design & problem-solving skills with one or more programming languages, such as Python, Java, C# or C++. Ability to work independently, influence others, and solid communication and collaboration skills. Familiarity with search engines, dealing with online instrumentation. Experience with large datasets and interest in consumer online search behaviours. Experience with building machine learning models on large scale data.

XML job scraping automation by YubHub

What you'll do

You will be responsible for developing new types of search index storage, including streaming and batch data processing systems in a high-load environment capable of handling billions of pages. You will also build new core search components, including algorithms for efficient retrieval and ranking, and push the limits of hardware performance.

• Develop new types of search index storage, including streaming and batch data processing systems in a high-load environment capable of handling billions of pages
• Build new core search components, including algorithms for efficient retrieval and ranking
• Push the limits of hardware performance

What you need

• 5+ years of hands-on experience in C++ development
• Knowledge of Python or other scripting languages
• Passion for writing clean, efficient, and scalable C++ code
• Strong knowledge of algorithms and data structures, and the ability to apply them effectively
• Deep understanding of multithreading, including various approaches, challenges, and trade-offs

Why this matters

This role is critical to building next-generation search products and technologies. You will help drive key decisions around the architecture, design, and implementation of foundational components in their technical stack.

XML job scraping automation by YubHub