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Remote Natural Language Processing engineer jobs

We, at Turing, are looking for talented remote Natural Language Processing (NLP) engineers who will be responsible for transforming natural language data into useful features using NLP techniques. Get a chance to work with top Silicon Valley companies and rise quickly through the ranks.

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Job description

Job responsibilities

  • Select appropriate annotated datasets for supervised learning methods
  • Use effective text representations to transform natural language into useful features
  • Find and implement the right algorithms and tools for NLP tasks
  • Design and develop NLP systems as per the requirements
  • Train the developed model and run evaluation experiments
  • Perform statistical analysis and refine models
  • Extend ML libraries and frameworks to apply in NLP tasks
  • Stay updated in the rapidly changing field of AI and ML

Minimum requirements

  • Bachelor’s/Master’s degree in Engineering, Computer Science, or IT (or equivalent experience)
  • 3+ years of experience as an NLP or Machine Learning engineer (rare exceptions for highly skilled developers)
  • Extensive knowledge of NLP techniques and algorithms
  • Experience working on text representation, semantic extraction techniques, data structures, and modeling
  • Experience with back-end technologies such as Python, Java, and R
  • Working knowledge of machine learning frameworks (like Keras or PyTorch) and libraries
  • Familiarity with big data frameworks such as Spark and Hadoop
  • Knowledge of text representation techniques, statistics, and classification algorithms
  • Fluent in English to communicate effectively
  • Ability to work full-time (40 hours/week) with a 4-hour overlap with US time zones

Preferred skills

  • Familiarity with machine translation and compilation
  • Knowledge of CI/CD pipelines, syntactic, and semantic parsing
  • Ability to write robust and testable code
  • Excellent analytical and interpersonal skills
  • Ability to work independently as well as with a team

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How to become a Natural Language Processing (NLP) engineer ?

Natural language processing (NLP) is a combination of computer science, information science, artificial intelligence (AI), and linguistics. The field of natural language processing (NLP) is concerned with the interaction between computers and human languages.

While computers excel at managing organized information, they require some assistance when dealing with human languages. There are hundreds of languages and dialects, each with its own set of grammatical rules, slang, terminology, and syntax.

Have you ever wondered how Google or Alexa can interpret your words? That's NLP at work! As a result, NLP Engineers are in charge of the programming that enables technology to interpret and evaluate natural language input.

Because of its ubiquity, NLP is a popular choice for companies wishing to start a web development project. Developers that have worked with these technologies before are in great demand. If you're on the fence about applying for remote Natural Language Processing developer jobs, you have many opportunities waiting for you.

What is the scope of Natural Language Processing development?

NLP will rise in popularity as the amount of available data keeps expanding, and algorithms become more complex and accurate. It's changing the way humans and robots interact with one another. The aforementioned applications of NLP demonstrate that it is a technology that significantly enhances our quality of life.

Unstructured information makes up as much as 80% of what we encounter. As a result, NLP is one of the most important topics of data science. Organizing this data is a significant task that various scholars are tackling on a daily basis. NLP is advancing at a rapid pace, and we may anticipate it to impact more and more facets of our life in the future.

Do you feel compelled to apply for remote Natural Language Processing (NLP) engineer jobs based on these recommendations? To discover more, let's go a little further into the duties and responsibilities.

What are the roles and responsibilities of a Natural Language Processing (NLP) engineer?

To design and construct the next generation of a company's mobile apps, Natural Language Processing (NLP) engineers cooperate with a team of skilled engineers. In order to produce the product, other app developments and technical teams collaborate closely with the developers.

A developer's key responsibilities after securing remote Natural Language Processing (NLP) engineer jobs are as follows:
System design and development for natural language processing

  • Define language learning datasets that are relevant.
  • Use powerful text representations to convert natural language into valuable characteristics.
  • Develop NLP systems in accordance with specifications.
  • Experiment with the created model and train it.
  • For NLP jobs, find and use the correct algorithms and tools.
  • Analyze the data statistically and improve the models
  • Maintain a constant level of knowledge in the field of machine learning.
  • Maintain NLP frameworks and libraries
  • Implement changes as needed and analyze bugs

How to become a Natural Language Processing (NLP) engineer?

Let's have a look at the processes to become a Natural Language Processing (NLP) engineer. To begin, keep in mind that working as a Natural Language Processing (NLP) engineer does not necessitate any academic degree. Whether you're a graduate or non-graduate, brilliant or inexperienced, you can grasp Natural Language Processing (NLP) and make a career out of it. Practical experience and understanding of appropriate technical and non-technical abilities are all that are required.

You may have heard, though, that remote Natural Language Processing (NLP) engineer jobs need a bachelor's or master's degree in computer science or a related field. This is true for a variety of reasons. For starters, you'll have a fundamental grasp of all technologies. Second, a degree guarantees a developer's competence in the subject, giving you an advantage over other applicants in interviews.

Let's take a look at some of the skills and methods that might help you acquire a job as a Natural Language Processing (NLP) engineer.

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Skills required to become a Natural Language Processing (NLP) engineer

To fetch high-paying Natural Language Processing (NLP) engineer jobs, the first step is to learn the following core skills.

1. Text Processing

Learning the most significant methods for text processing is one of the most important ideas to deal with in programming languages. Working with strings in a computer language should come naturally to you; understanding how to manipulate text back and forth, utilizing regular expressions, and slicing strings are just a few of the most critical skills to have while working in Natural Language Processing. Therefore, be familiar with the text process to land the best remote Natural Language Processing (NLP) engineer jobs

2. NLTK Library

Natural Language Toolkit Library, or NLTK, is one of the earliest Natural Language Processing libraries available. But the library, which was initially published 20 years ago, is one of the greatest tools for understanding some of the principles of NLP. The following are some of the library's well-organized resources:

  • Stemmers range in complexity from elementary to complicated.
  • Splitting your corpus into sentences or words is possible with tokenizers.
  • Part-of-Speech taggers include both off-the-shelf and bespoke frequency taggers.
  • Lemmatization of words.
  • N-Grams are a set of notions.

In most NLP applications, these ideas are essential for understanding text normalization and text processing. Understanding the NLTK library will allow you to learn the abilities needed to create an NLP pipeline from the ground up. Even if you don't use these strategies in your NLP pipelines, having these tools in your toolbox is always a good idea. If you learn how to use them, impressing recruiters for remote Natural Language Processing (NLP) engineer jobs will be a cakewalk for you.

3. Reading Text Data

In the last decade, the massive volume of text data traveling on the internet has expanded tremendously. Aside from gathering data from the internet, NLP practitioners (like most data scientists) must deal with a variety of files in various formats.

Anyone working in NLP should be able to read text data from a variety of sources; for example, CSV and JSON files are standard text corpus formats that must be imported into your workspace before you can start working on your NLP application.

4. Word Vectors

Word vectors are one of the most essential strategies in NLP today, and they're also very helpful in understanding how Artificial Neural Networks are employed in NLP.

Understanding and studying most Word Vectors is vital not just for NLP, but also for general Machine Learning. You will be exposed to the inner working mechanics of Neural Networks, one of the most significant models in machine learning today, through learning them. Backpropagation, weight optimization, activation functions, and gradient descent will all be covered, which should give you an excellent head start on running and building numerous Neural Network models. Therefore, during the recruitment for remote Natural Language Processing (NLP) engineer jobs, technical recruiters always test NLP engineers' knowledge on this and how developers used these for previous projects.

5. Recurrent Neural Networks

Text creation is another area of Natural Language Processing that has seen significant advancements because of the use of Neural Networks.

The design of Neural Networks used in text production differs from that used in Word Vectors or Text Classification. Known as Recurrent Neural Networks, these forms of NNs have many methods for storing and updating data that is typical of chained data like sentences.

Interested in remote Natural Language Processing (NLP) engineer jobs?

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Apply now

How to get remote Natural Language Processing (NLP) engineer jobs?

Athletes and Natural Language Processing (NLP) engineers share many similarities. They must practice successfully and on a regular basis in order to be the greatest in their field. They should also put in enough effort to improve their talents over time. When practicing, Natural Language Processing (NLP) engineers should enlist the support of a Natural Language Processing (NLP) expert who is successful in the area, as well as employ more effective practice strategies. Knowing how much to practice as a Natural Language Processing (NLP) engineer is critical. So enlist the services of a Natural Language Processing (NLP) engineer and keep an eye out for burnout indications!

Turing provides the top remote Natural Language Processing (NLP) engineer jobs to help you reach your professional goals as a Natural Language Processing (NLP) engineer. We allow you to work on challenging technical and business challenges utilizing cutting-edge technology, allowing you to swiftly enhance your abilities. Get full-time, long-term remote Natural Language Processing (NLP) engineer employment with greater income and professional progress by joining a network of the world's greatest Natural Language Processing (NLP) engineers.

Why become a Natural Language Processing (NLP) engineer at Turing?

Elite US jobs
Career growth
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Once you join Turing, you’ll never have to apply for another job.
Work from the comfort of your home
Great compensation

How much does Turing pay their Natural Language Processing (NLP) engineers?

Every Natural Language Processing (NLP) engineer at Turing has the ability to select their own pace. Turing, on the other hand, will suggest a wage to the Natural Language Processing (NLP) engineer that we believe will provide you with a rewarding and long-term opportunity. Our compensation suggestions are based on our research into market conditions as well as consumer desire.

Frequently Asked Questions

Turing is an AGI infrastructure company specializing in post-training large language models (LLMs) to enhance advanced reasoning, problem-solving, and cognitive tasks. Founded in 2018, Turing leverages the expertise of its globally distributed technical, business, and research experts to help Fortune 500 companies deploy customized AI solutions that transform operations and accelerate growth. As a leader in the AGI ecosystem, Turing partners with top AI labs and enterprises to deliver cutting-edge innovations in generative AI, making it a critical player in shaping the future of artificial intelligence.

After uploading your resume, you will have to go through the three tests -- seniority assessment, tech stack test, and live coding challenge. Once you clear these tests, you are eligible to apply to a wide range of jobs available based on your skills.

No, you don't need to pay any taxes in the U.S. However, you might need to pay taxes according to your country’s tax laws. Also, your bank might charge you a small amount as a transaction fee.

We, at Turing, hire remote developers for over 100 skills like React/Node, Python, Angular, Swift, React Native, Android, Java, Rails, Golang, PHP, Vue, among several others. We also hire engineers based on tech roles and seniority.

Communication is crucial for success while working with American clients. We prefer candidates with a B1 level of English i.e. those who have the necessary fluency to communicate without effort with our clients and native speakers.

Currently, we have openings only for the developers because of the volume of job demands from our clients. But in the future, we might expand to other roles too. Do check out our careers page periodically to see if we could offer a position that suits your skills and experience.

Our unique differentiation lies in the combination of our core business model and values. To advance AGI, Turing offers temporary contract opportunities. Most AI Consultant contracts last up to 3 months, with the possibility of monthly extensions—subject to your interest, availability, and client demand—up to a maximum of 10 continuous months. For our Turing Intelligence business, we provide full-time, long-term project engagements.

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Ideally, a remote developer needs to have at least 3 years of relevant experience to get hired by Turing, but at the same time, we don't say no to exceptional developers. Take our test to find out if we could offer something exciting for you.

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Product Owner – Operations & Controls Platform (Back Office Operations & Global Business Finance)

Product Owner – Operations & Controls Platform (Back Office Operations & Global Business Finance)


Full-Time - Location: New York, NY


About Turing:

Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems.

Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies


About the Role

We are looking for an experienced Product Owner to lead the strategy, roadmap, and execution for platforms supporting Back Office Operations and Global Business Finance. The ideal candidate brings strong product management experience combined with deep knowledge of financial operations, operational controls, and controller functions.

This role will partner closely with business stakeholders, engineering, and operations teams to modernize back-office platforms and improve operational efficiency. While familiarity with AI is important, the primary focus is on delivering business value through well-designed operational systems rather than building AI solutions.


Key Responsibilities

  • Own the product vision, roadmap, and prioritization for Operations & Controls platforms.
  • Lead product discovery by understanding business problems, operational workflows, and stakeholder requirements.
  • Partner with Back Office Operations, Controllers, Finance, and Technology teams to improve operational processes.
  • Drive modernization initiatives across reconciliation, financial controls, exception management, workflow automation, and operational reporting.
  • Build and manage the product backlog, define user stories, and prioritize features based on business value.
  • Coordinate delivery across engineering, architecture, and business stakeholders.
  • Track milestones, dependencies, risks, and delivery progress.
  • Promote transparency and effective stakeholder communication throughout the product lifecycle.
  • Identify practical opportunities where AI and automation tools can improve productivity, decision-making, and operational efficiency.
  • Ensure solutions meet governance, audit, and operational control requirements.

Required Qualifications

  • 7+ years of experience as a Product Owner, Product Manager, or Senior Business Analyst within Financial Services.
  • Strong experience supporting Back Office Operations, Controllers, Finance Operations, Treasury, or Investment Operations.
  • Experience with cash reconciliation, position reconciliation, operational controls, controller workflows, or financial close processes.
  • Experience building or enhancing corporate back-office platforms and operational systems.
  • Strong understanding of operational risk, controls, reconciliation processes, and governance.
  • Excellent stakeholder management and cross-functional collaboration skills.
  • Proven ability to manage product roadmaps, planning, prioritization, and execution.
  • Strong analytical, communication, and problem-solving skills.
  • Familiarity with AI tools (e.g., ChatGPT, Copilot, Gemini) and understanding of where AI can improve operational workflows. Hands-on AI solution development is not required.
  • Ability to work effectively with engineering teams and understand modern software delivery practices.

Nice to Have

  • Experience with platforms such as Geneva, Arcesium, Investran, Kyriba, or similar fund accounting and operations systems.
  • Experience working with fund administrators or investment operations teams.
  • Background in treasury, controller organizations, finance transformation, or operations transformation.
  • Experience with Agile product delivery.
  • Exposure to workflow automation, cloud platforms, or modern enterprise applications.

Ideal Candidate Profile

The ideal candidate has experience leading products for finance or operations organizations, understands how controllers and back-office teams operate, and can translate business needs into scalable product solutions. They are comfortable working with AI-enabled tools and understand where AI can add value but are not required to have built AI products or machine learning solutions.


Finance
251-10K employees
Product ManagementAsset ManagementMachine Learning+ 2
briefcase
Technical / Functional Business Analyst – Back Office Operations & Global Business Finance

Technical / Functional Business Analyst – Back Office Operations & Global Business Finance


Location: New York, New York


About Turing:

Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems.

Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies


Team

Back Office Operations & Global Business Finance Technology


About the Role

We are a global team of alternative investment managers passionate about delivering uncommon value to our investors and shareholders. With over 30 years of expertise across Private Equity, Credit, and Real Assets, we are known for our integrated businesses, strong investment performance, value-oriented philosophy, and exceptional people.

We are looking for a Technical / Functional Business Analyst who understands both business operations and technology, with particular exposure to Controllers, Finance Operations, or Back Office environments. This role is ideal for someone who can work closely with business stakeholders, translate operational processes into clear requirements, and partner with engineering teams to deliver scalable enterprise solutions.

The ideal candidate has experience working on corporate back-office platforms supporting finance or operations functions, understands reconciliation and control processes, and is comfortable using modern AI tools to improve productivity and documentation.

This role begins as a consulting engagement with a right-to-hire path.


Key Responsibilities

  • Partner with Controllers, Operations, Finance, and Technology teams to understand business processes, pain points, and operational controls.
  • Analyze current-state workflows involving:
    • Cash reconciliation
    • Position reconciliation
    • Operational controls
    • Exceptions management
    • Approval workflows
    • Financial operations
  • Translate business requirements into:
    • Business process flows
    • Functional specifications
    • User stories
    • Acceptance criteria
    • Data requirements
  • Facilitate workshops and requirement gathering sessions with business stakeholders.
  • Work closely with Product Owners and Engineering teams to clarify requirements, prioritize work, and remove ambiguity.
  • Support UAT planning, test scenarios, and business validation.
  • Maintain end-to-end traceability between business requirements, technical implementation, and delivered functionality.
  • Document business processes and recommend improvements to increase efficiency and strengthen operational controls.
  • Use AI productivity tools (ChatGPT, Microsoft Copilot, Gemini, etc.) to accelerate documentation, analysis, summarization, and research while validating outputs for accuracy and compliance.

Required Qualifications

  • 5+ years of experience as a Business Analyst, Functional Analyst, or Technical BA delivering enterprise software solutions.
  • Experience working in Financial Services, Asset Management, Investment Banking, Banking, Insurance, or Corporate Finance environments.
  • Strong familiarity with Controllers or Back Office Operations.
  • Experience with one or more of the following:
    • Cash reconciliation
    • Position reconciliation
    • Trade operations
    • Financial controls
    • Accounting operations
    • Operations support functions
  • Excellent requirements gathering, process mapping, and stakeholder management skills.
  • Comfortable working with engineers and discussing:
    • APIs
    • Data flows
    • System integrations
    • Basic database concepts
  • Strong analytical thinking with the ability to identify process gaps and operational risks.
  • Excellent written and verbal communication skills.
  • Ability to balance business priorities with technical constraints.

Nice to Have

  • Experience supporting Controllers, Finance, Treasury, Accounting, or Operations organizations.
  • Experience implementing or enhancing corporate back-office systems.
  • Basic SQL knowledge for analysis and reporting.
  • Familiarity with Agile delivery methodologies.
  • Exposure to workflow automation platforms, BPM tools, or event-driven architectures.
  • Experience working with enterprise ERP or financial platforms.
  • Understanding of audit, governance, compliance, and operational risk processes.
  • Experience using AI tools to improve productivity and documentation (hands-on AI solution development is not required).

Why Join

  • Work on strategic platforms supporting critical Finance and Operations functions.
  • Partner directly with business leaders, Product Managers, and Engineering teams.
  • Help modernize enterprise back-office systems that improve operational efficiency and financial controls.
  • Build expertise in highly scalable financial technology platforms while leveraging AI as a productivity accelerator.
  • Join a collaborative team focused on practical execution, operational excellence, and continuous improvement.
Finance
251-10K employees
Business AnalysisAsset ManagementAPI Design+ 2
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