Hire the Top 2% of
Remote Google Document AI Developers
in the United Kingdom

Your trusted source for top remote Google Document AI developers, engineers, expert programmers, freelancers, and consultants in the United Kingdom — Perfect for startups and enterprises.

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215 Remote Google Document AI developers and experts available to hire:

Google Document AI expert - Reza J.
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Reza J.

Vetted Google Document AI developer in the United Kingdom

Reza is an accomplished CTO and engineer with extensive experience in near-silicon design and problem-solving. He has done stream processing in all kinds of domains, using MQTT-SN, HL7 in healthcare, and mSEED and SEGY in earthquake analysis, utilizing a wide array of databases and programming languages. Passionate about building, Reza has maintained projects such as Ansible, universal-ctags, and QMK, and contributed to the Linux kernel and EDKII (UEFI).

Google Cloud PlatformGoogle Document AIFull StackDevOpsSecurity engineeringAnsibleRuby on RailsPythonAWSMLOpsKubernetesLLMNode.jsMongoDBAzureComputer VisionRabbitMQNLPAWS LambdaSpacyCI/CDAzure FunctionsRESTful APITailwind cssLangchainRetrieval-Augmented GenerationPostgreSQLRedisTime Series ModelingOpenShiftApache KafkaCephTerraformTensorFlowPyTorchVue.jsPyPIpytestGlusterfsGitLab CI/CD
+33
Python, AWS, MLOps, Kubernetes, LLM, Node.js, MongoDB, Azure, Computer Vision, RabbitMQ, NLP, AWS Lambda, Spacy, CI/CD, Azure Functions, RESTful API, Tailwind css, Langchain, Retrieval-Augmented Generation, PostgreSQL, Redis, Time Series Modeling, OpenShift, Apache Kafka, Ceph, Terraform, TensorFlow, PyTorch, Vue.js, PyPI, pytest, Glusterfs, GitLab CI/CD
Google Document AI developers developer - Reza J.'s portfolio image
Google Document AI architect - VINOD M.
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VINOD M.

Vetted Google Document AI developer in the United Kingdom

An experienced data scientist with extensive technical proficiency and a consulting background gained from diverse projects across medical, retail, consumer, space, and energy domains. My focus lies in applying data science to tackle complex challenges and providing innovative solutions that yield significant business outcomes. I possess a distinctive combination of technical prowess and strategic thinking, underpinned by a robust foundation in fields like statistical analysis, machine learning, deep learning, NLP etc. Currently, I am actively pursuing challenging opportunities to further enhance my technical skills, aiming to contribute to a forward-thinking organization where my expertise can propel development and technological advancement.

AI • 3 yrsGoogle BigQueryGoogle Cloud PlatformNLPMachine learningPythonStatistical AnalysisPower BIDeep LearningTensorFlowComputer VisionData ScienceAirflowSQLLinuxDatabase DevelopmentJD Edwards E1 Programming
+10
Power BI, Deep Learning, TensorFlow, Computer Vision, Data Science, Airflow, SQL, Linux, Database Development, JD Edwards E1 Programming
Google Document AI programmer - Adi S.
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Adi S.

Vetted Google Document AI developer in the United Kingdom

**python jedi** with baby yoda skills @ JS, React, Redux. I am a senior software engineer @ Pinterest with over a decade of software engineering experience with B2B and B2C products in large and startups alike. I have extensive experience building large scale systems which solve real world problems and bring in up to billions of dollars in revenue. I have a bachelor's and master's degree in computer science with a specialization in Machine Learning and have been coding for the last 17 odd years. Outside of work, I like to cycle, take portraits and workout regularly.

Startup experienceApache Airflow • 5 yrsGoogle BigQueryGoogle pubsubAirflowGoogle DataflowPython 3Node.jsPythonReactDockerKubernetesGoReduxJavaHTML/CSSJavaScriptMachine learningScrum MasterLuigiAgile
+13
Python, React, Docker, Kubernetes, Go, Redux, Java, HTML/CSS, JavaScript, Machine learning, Scrum Master, Luigi, Agile
Google Document AI architect - Jose R.
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Jose R.

Vetted Google Document AI developer in the United Kingdom (UTC+1)

I hold an MSc in Industrial Engineering and throughout the years I have created and deployed chatbots, recommender systems, decision, classification and forecasting models as well as many processing pipelines. On the different teams I have collaborated or lead, I have always promoted best practices and I have held mentoring sessions to learn the basics or discover new technologies. Proficient in Python, NLP, ML Ops, and various ML tools, including the major cloud providers.

AI • 10 yrsGoogle BigQueryGoogle DataflowAI/MLPythonLLMFlaskAPINLPChatbotPrompt EngineeringLarge Language ModelsRetrieval-Augmented GenerationGitCloudJiraDockerKubernetesTerraformApache BeamDBTPostgreSQLGitHubNeo4jElasticsearchCI/CDDrone OperatorAWS
+21
API, NLP, Chatbot, Prompt Engineering, Large Language Models, Retrieval-Augmented Generation, Git, Cloud, Jira, Docker, Kubernetes, Terraform, Apache Beam, DBT, PostgreSQL, GitHub, Neo4j, Elasticsearch, CI/CD, Drone Operator, AWS
Google Document AI engineer - Vincent L.
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Vincent L.

Vetted Google Document AI developer in the United Kingdom

Senior Data Engineer with 5 years experience working with the Google Cloud Platform, and various supplementary technologies (see work experience section for more detail). My data journey started through UCL business management and data science course, gradually grew my interest toward the technical side of things via my first job as a data analyst, eventually led me to become a developer in the world of data engineering, and further promoted to the role of senior data engineer.

Google Cloud Platform • 5 yrsApache AirflowSQLPythonData modelingData warehouseTerraformData Visualization
+1
Data Visualization
Google Document AI architect - Williams M.
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Williams M.

Vetted Google Document AI developer in the United Kingdom (UTC+1)

I am a Machine Learning/DevOps engineer with great experience building reliable and highly available platforms that scale and ensures uptime needed for customer satisfaction. I am knowledgeable of the CAP theorem, PECELC theorem, advanced systems design, data partitioning, application and infrastructure level monitoring and improving latency of requests. One of my proudest achievements was improving the uptime of an infrastructure from 79% to 99.99%. I am skilled in kubernetes, python, terraform, Jenkins, AWS, GCP, ansible, docker and always apply best practices like preventing escalating privileges, scanning images before deploy, using secrets correctly. I am also a certified kubernetes application developer. I am also a Senior Full stack developer, I have developed multiple apis with TypeScript and Nestjs. I have built web applications with ReactJs and mobile applications with Flutter and React Native.

AI • 6 yrsGoogle Cloud Platform • 3 yrsPythonDockerKubernetesDevOpsJavaScriptReact NativeAWSTensorFlowNLPDjangoMachine learningNode.jsReactTypeScriptContinuous IntegrationPyTorchAzureFlutterTerraformBashJenkinsGrafanaPrometheusAWS EKSHelm ChartsDocker & KubernetesArgo CDNotionLDAPGraphQLHelmGitLab CI/CDAnsibleBlockchain
+29
React Native, AWS, TensorFlow, NLP, Django, Machine learning, Node.js, React, TypeScript, Continuous Integration, PyTorch, Azure, Flutter, Terraform, Bash, Jenkins, Grafana, Prometheus, AWS EKS, Helm Charts, Docker & Kubernetes, Argo CD, Notion, LDAP, GraphQL, Helm, GitLab CI/CD, Ansible, Blockchain
Google Document AI engineer - Srinivas (.
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Srinivas (.

Vetted Google Document AI developer in the United Kingdom

Most of my work for customers is around solving complex business problems through people and technology. Expertise in Front-end user interfaces, interactions through back-end APIs and servers, middleware, data storage and integration Strong experience in ASP.NET Core development.

Google ads • 8 yrsGenerative AI • 1 yrsSQLSQL Server 2008VB.NETASP.NET CoreC#Azure Data EngineerAzureHTML/CSSAngularEntity FrameworkMicrosoft SQL ServerSsrs 2008Visual Basic
+8
Azure Data Engineer, Azure, HTML/CSS, Angular, Entity Framework, Microsoft SQL Server, Ssrs 2008, Visual Basic
Google Document AI programmer - CHIBUZOR O.
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CHIBUZOR O.

Vetted Google Document AI developer in the United Kingdom

As a Backend Developer and DevOps Engineer with extensive experience in web development, I specialize in building scalable and robust backend systems. My expertise includes JavaScript, TypeScript, Go, Node.js/Express, MongoDB, SQL, AWS, GCP, Docker, Terraform, and Kubernetes. I also have frontend development experience with Angular, having worked on multiple projects building interactive and user-friendly interfaces. I am passionate about delivering high-quality code and maintaining robust and scalable systems. I am always eager to take on new challenges and to collaborate with cross-functional teams to deliver successful projects.

Google Cloud Platform • 3 yrsAirtableGoogle Cloud FunctionsNode.jsGoAWSSQLTypeScriptServerlessPostgreSQLRedisFirestoreAngular 6
+6
TypeScript, Serverless, PostgreSQL, Redis, Firestore, Angular 6
Google Document AI architect - ayoola M.
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ayoola M.

Vetted Google Document AI developer in the United Kingdom

Data Engineer with over 5 years of experience in developing Python-based solutions and leveraging Machine Learning algorithms to address complex challenges. I have a strong background in Data Integration, Data Warehousing, Data Modelling, and Data Quality. I excel at implementing and maintaining both batch and streaming Big Data pipelines with automated workflows. My expertise lies in driving data-driven insights, optimizing processes, and delivering value to businesses through a comprehensive understanding of data engineering principles and best practices. KEY SKILLS Python | SQL | PySpark | JavaScript | Google cloud platform (GCP) | Azure | Amazon web services (AWS) | TensorFlow | Keras | ETL | ELT | DBT | BigQuery | BigTable | Redshift | Snowflake | Data warehouse | Data Lake | Data proc | Data Flow | Data Fusion | Data prep | Pubsub | Looker | Data studio | Data factory | Databricks | Auto ML | Vertex AI | Pandas | Big Data | Numpy | Dask | Apache Beam | Apache Airflow | Azure Synapse | Cloud Data Loss Prevention | Machine Learning | Deep learning | Kafka | Scikit Learn | Data visualisation | Tableau | Power BI | Django | Git | GitLab |

Airflow • 4 yrsGoogle BigQuery • 3 yrsGoogle Cloud Platform • 3 yrsApache AirflowPythonApache KafkaSQLTerraformPower BIETLCI/CDData Engineering
+5
Terraform, Power BI, ETL, CI/CD, Data Engineering
Google Document AI programmer - Juan J.
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Juan J.

Vetted Google Document AI developer in the United Kingdom

Creative Senior Software Engineer with over 8 years of experience developing scalable data-driven applications. Expertise in building teams, automating processes, and providing enterprise-class solutions in cloud-native environments. Love to build effective, secure, and resilient systems.

Google Cloud PlatformAIPythonMySQLCI/CDAWSScrapyDjangoNode.jsGitFlaskPostgreSQLGitHubJenkinsWeb ScrapingPython 3ReactSystem designWeb CrawlingTerraformNestJSFastapiHTML/CSSMachine learningAnalyticsEmber.jsJavaScriptCircleciVue.jsChaliceC#AzurePandasDockerMicrosoft SQL ServerKubernetes.NET Core.NET FrameworkApache Airflow
+32
Django, Node.js, Git, Flask, PostgreSQL, GitHub, Jenkins, Web Scraping, Python 3, React, System design, Web Crawling, Terraform, NestJS, Fastapi, HTML/CSS, Machine learning, Analytics, Ember.js, JavaScript, Circleci, Vue.js, Chalice, C#, Azure, Pandas, Docker, Microsoft SQL Server, Kubernetes, .NET Core, .NET Framework, Apache Airflow

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Why clients hire Google Document AI developers with Arc

Without Arc by my side, I would be wasting a lot of time looking for and vetting talent. I'm not having to start a new talent search from scratch. Instead, I’m able to leverage the talent pool that Arc has created.
Mitchum Owen
Mitchum Owen
President of Milo Digital
The process of filling our position took less than a week and they found us a superstar. They've had the flexibility to meet our specific needs every step of the way and their customer service has been top-notch since day one.
Matt Gysel
Matt Gysel
Finance & Strategy at BaseVenture
The biggest advantage and benefit of working with Arc is the tremendous reduction in time spent sourcing quality candidates. We’re able to identify the talent in a matter of days.
Philip Tsai
Philip Tsai
Director of Engineering at Chegg

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Freelance Google Document AI developers in the United Kingdom

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FAQs

Why hire a Google Document AI developer?

In today’s world, most companies have code-based needs that require developers to help build and maintain. For instance, if your business has a website or an app, you’ll need to keep it updated to ensure you continue to provide positive user experiences. At times, you may even need to revamp your website or app. This is where hiring a developer becomes crucial.

Depending on the stage and scale of your product and services, you may need to hire a Google Document AI developer, multiple engineers, or even a full remote developer team to help keep your business running. If you’re a startup or a company running a website, your product will likely grow out of its original skeletal structure. Hiring full-time remote Google Document AI developers can help keep your website up-to-date.

How do I hire Google Document AI developers?

To hire a Google Document AI developer, you need to go through a hiring process of defining your needs, posting a job description, screening resumes, conducting interviews, testing candidates’ skills, checking references, and making an offer.

Arc offers three services to help you hire Google Document AI developers effectively and efficiently. Hire full-time Google Document AI developers from a vetted candidates pool, with new options every two weeks, and pay through prepaid packages or per hire. Alternatively, hire the top 2.3% of expert freelance Google Document AI developers in 72 hours, with weekly payments.

If you’re not ready to commit to the paid plans, our free job posting service is for you. By posting your job on Arc, you can reach up to 450,000 developers around the world. With that said, the free plan will not give you access to pre-vetted Google Document AI developers.

Furthermore, we’ve partnered with compliance and payroll platforms Deel and Remote to make paperwork and hiring across borders easier. This way, you can focus on finding the right Google Document AI developers for your company, and let Arc handle the logistics.

Where do I hire the best remote Google Document AI developers?

There are two types of platforms you can hire Google Document AI developers from: general and niche marketplaces. General platforms like Upwork, Fiverr, and Gigster offer a variety of non-vetted talents unlimited to developers. While you can find Google Document AI developers on general platforms, top tech talents generally avoid general marketplaces in order to escape bidding wars.

If you’re looking to hire the best remote Google Document AI developers, consider niche platforms like Arc that naturally attract and carefully vet their Google Document AI developers for hire. This way, you’ll save time and related hiring costs by only interviewing the most suitable remote Google Document AI developers.

Some factors to consider when you hire Google Document AI developers include the platform’s specialty, developer’s geographical location, and the service’s customer support. Depending on your hiring budget, you may also want to compare the pricing and fee structure.

Make sure to list out all of the important factors when you compare and decide on which remote developer job board and platform to use to find Google Document AI developers for hire.

How do I write a Google Document AI developer job description?

Writing a good Google Document AI developer job description is crucial in helping you hire Google Document AI developers that your company needs. A job description’s key elements include a clear job title, a brief company overview, a summary of the role, the required duties and responsibilities, and necessary and preferred experience. To attract top talent, it's also helpful to list other perks and benefits, such as flexible hours and health coverage.

Crafting a compelling job title is critical as it's the first thing that job seekers see. It should offer enough information to grab their attention and include details on the seniority level, type, and area or sub-field of the position.

Your company description should succinctly outline what makes your company unique to compete with other potential employers. The role summary for your remote Google Document AI developer should be concise and read like an elevator pitch for the position, while the duties and responsibilities should be outlined using bullet points that cover daily activities, tech stacks, tools, and processes used.

For a comprehensive guide on how to write an attractive job description to help you hire Google Document AI developers, read our Engineer Job Description Guide & Templates.

What skills should I look for in a Google Document AI developer?

The top five technical skills Google Document AI developers should possess include proficiency in programming languages, understanding data structures and algorithms, experience with databases, familiarity with version control systems, and knowledge of testing and debugging.

Meanwhile, the top five soft skills are communication, problem-solving, time management, attention to detail, and adaptability. Effective communication is essential for coordinating with clients and team members, while problem-solving skills enable Google Document AI developers to analyze issues and come up with effective solutions. Time management skills are important to ensure projects are completed on schedule, while attention to detail helps to catch and correct issues before they become bigger problems. Finally, adaptability is crucial for Google Document AI developers to keep up with evolving technology and requirements.

What kinds of Google Document AI developers are available for hire through Arc?

You can find a variety of Google Document AI developers for hire on Arc! At Arc, you can hire on a freelance, full-time, part-time, or contract-to-hire basis. For freelance Google Document AI developers, Arc matches you with the right senior developer in roughly 72 hours. As for full-time remote Google Document AI developers for hire, you can expect to make a successful hire in 14 days. To extend a freelance engagement to a full-time hire, a contract-to-hire fee will apply.

In addition to a variety of engagement types, Arc also offers a wide range of developers located in different geographical locations, such as Latin America and Eastern Europe. Depending on your needs, Arc offers a global network of skilled engineers in various different time zones and countries for you to choose from.

Lastly, our remote-ready Google Document AI developers for hire are all mid-level and senior-level professionals. They are ready to start coding straight away, anytime, anywhere.

Why is Arc the best choice for hiring Google Document AI developers?

Arc is trusted by hundreds of startups and tech companies around the world, and we’ve matched thousands of skilled Google Document AI developers with both freelance and full-time jobs. We’ve successfully helped Silicon Valley startups and larger tech companies like Spotify and Automattic hire Google Document AI developers.

Every Google Document AI developer for hire in our network goes through a vetting process to verify their communication abilities, remote work readiness, and technical skills. Additionally, HireAI, our GPT-4-powered AI recruiter, enables you to get instant candidate matches without searching and screening.

Not only can you expect to find the most qualified Google Document AI developer on Arc, but you can also count on your account manager and the support team to make each hire a success. Enjoy a streamlined hiring experience with Arc, where we provide you with the developer you need, and take care of the logistics so you don’t need to.

How does Arc vet a Google Document AI developer's skills?

Arc has a rigorous and transparent vetting process for all types of developers. To become a vetted Google Document AI developer for hire on Arc, developers must pass a profile screening, complete a behavioral interview, and pass a technical interview or pair programming.

While Arc has a strict vetting process for its verified Google Document AI developers, if you’re using Arc’s free job posting plan, you will only have access to non-vetted developers. If you’re using Arc to hire Google Document AI developers, you can rest assured that all remote Google Document AI developers have been thoroughly vetted for the high-caliber communication and technical skills you need in a successful hire.

How long does it take to find Google Document AI developers on Arc?

Arc pre-screens all of our remote Google Document AI developers before we present them to you. As such, all the remote Google Document AI developers you see on your Arc dashboard are interview-ready candidates who make up the top 2% of applicants who pass our technical and communication assessment. You can expect the interview process to happen within days of posting your jobs to 450,000 candidates. You can also expect to hire a freelance Google Document AI developer in 72 hours, or find a full-time Google Document AI developer that fits your company’s needs in 14 days.

Here’s a quote from Philip, the Director of Engineering at Chegg:

“The biggest advantage and benefit of working with Arc is the tremendous reduction in time spent sourcing quality candidates. We’re able to identify the talent in a matter of days.”

Find out more about how Arc successfully helped our partners in hiring remote Google Document AI developers.

How much does a freelance Google Document AI developer charge per hour?

Depending on the freelance developer job board you use, freelance remote Google Document AI developers' hourly rates can vary drastically. For instance, if you're looking on general marketplaces like Upwork and Fiverr, you can find Google Document AI developers for hire at as low as $10 per hour. However, high-quality freelance developers often avoid general freelance platforms like Fiverr to avoid the bidding wars.

When you hire Google Document AI developers through Arc, they typically charge between $60-100+/hour (USD). To get a better understanding of contract costs, check out our freelance developer rate explorer.

How much does it cost to hire a full time Google Document AI developer?

According to the U.S. Bureau of Labor Statistics, the medium annual wage for developers in the U.S. was $120,730 in May 2021. What this amounts to is around $70-100 per hour. Note that this does not include the direct cost of hiring, which totals to about $4000 per new recruit, according to Glassdoor.

Your remote Google Document AI developer’s annual salary may differ dramatically depending on their years of experience, related technical skills, education, and country of residence. For instance, if the developer is located in Eastern Europe or Latin America, the hourly rate for developers will be around $75-95 per hour.

For more frequently asked questions on hiring Google Document AI developers, check out our FAQs page.

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