Best AI tools for< Find New Job >

Hella Jobs is a leading platform for AI, Machine Learning, and Data Science jobs. It connects job seekers with top employers in the field of AI/ML, allowing employers to post open jobs and hire top talent. Job seekers can create profiles, submit resumes, and find new job opportunities. The platform offers features such as job filtering by keywords and location, job category selection, salary range selection, and job type filtering. Hella Jobs aims to streamline the job search process for both employers and job seekers in the AI/ML industry.

Careerflow is a free AI-powered job search platform that provides a suite of tools and resources to help job seekers land their dream jobs faster. The platform includes an AI resume builder, LinkedIn profile optimizer, mock interview tool, job tracker, and more. Careerflow is designed to help job seekers save time and effort in their job search, and to increase their chances of getting hired at their dream companies.

My CV Creator is an online resume builder with AI assistance that helps users create professional-quality resumes, cover letters, and resume websites in minutes. The platform offers a range of features including pre-written examples, expert tips, and a flexible text editor. My CV Creator is designed to make the resume writing process faster and easier, and to help users stand out from the competition.

Candle is a career assistant platform that provides personalized guidance and intelligence to help individuals learn and earn more. It offers job search assistance, skills coaching, and career advice. Candle's mission is to transform opportunity for everyone with its unique AI platform that puts the power of a 24/7 career assistant into the hands of talent, globally.

JobWharf.ai is an AI-powered job application platform that helps users apply for jobs by submitting their CVs to various companies and startups. The platform offers a wide range of job opportunities in different categories and regions, with features like refining job searches, sending job applications on behalf of users, and providing CV optimization services. JobWharf.ai aims to simplify the job hunting process and increase users' chances of getting hired by matching their career goals with suitable employment opportunities.

Hirebase is an AI-powered job search engine that provides ultra-fresh job market data directly from company pages. It uses AI to scan 100,000 jobs in real-time, ensuring that every job listed is actively hiring on the internet. Users can receive email alerts for new job listings based on their preferences for job title, keywords, location, experience level, date posted, salary range, and more. Hirebase aims to 'unsuckify' the job search process by leveraging AI technology to streamline and enhance the job hunting experience.

Dribbble is a platform that connects designers with potential clients. It allows designers to showcase their work, find new clients, and get feedback from other designers. Dribbble also offers a variety of resources for designers, including tutorials, articles, and job listings.

UpCat is an AI-powered assistant that helps freelancers on Upwork write better proposals and find more jobs. It uses artificial intelligence to analyze your skills and experience, and then generates personalized proposals that are tailored to each job you apply for. UpCat also provides real-time alerts for new jobs that match your skills, so you can be the first to apply. With UpCat, you can save time and effort on your job search, and increase your chances of success on Upwork.

Climate Change AI is a community platform dedicated to leveraging artificial intelligence to address the challenges of climate change. The platform serves as a hub for researchers, practitioners, and policymakers to collaborate, share knowledge, and develop AI solutions for mitigating the impacts of climate change. By harnessing the power of AI technologies, Climate Change AI aims to accelerate the transition to a sustainable and resilient future.

Mo Ai Jobs is a job board for artificial intelligence (AI) professionals. It lists jobs in machine learning, engineering, research, data science, and other AI-related fields. The site is designed to help AI professionals find jobs at next-generation AI companies. Mo Ai Jobs is a valuable resource for anyone looking for a job in the AI industry.

Coach is an AI-powered career development platform designed for learners, job seekers, and career shifters. It offers personalized career guidance, resources for skills development, and assistance in exploring various career paths. Built by CareerVillage and a coalition of educators and nonprofits, Coach aims to provide trustworthy AI career advising and support for individuals at every stage of their career journey.

LinkedIn is a professional networking site that helps users connect with other professionals, find jobs, and learn new skills. It is also a platform for businesses to post jobs and find candidates. LinkedIn uses AI to power many of its features, such as its job search algorithm and its personalized content recommendations.

DAWN AI is an EDtech platform that is revolutionizing education with blockchain and AI. It is designed to make education accessible to everyone, regardless of their location, language, or abilities. DAWN offers a complete suite of blockchain-scaling solutions, including course transcription, AI recruitment services, a dyslexia-friendly platform, closed captioning and sign language interpretation, and tokenized affiliate marketing. It also has a Learn and Earn program in the metaverse, where learners can earn tokens by completing educational challenges and tasks in virtual worlds.

LinkedIn is a professional networking site that helps users connect with other professionals in their field, find jobs, and learn new skills. It also provides a platform for users to share articles, insights, and updates on their work and career. LinkedIn is a valuable tool for anyone looking to advance their career or stay up-to-date on the latest industry trends.

Collato is an AI assistant designed to help product teams save time on writing documents, answering questions, and generating new content. It can find, summarize, and generate new content based on your own product knowledge, saving you hours in manual work. Collato is also self-hosted, so you can keep your data private and secure.

ResumeBuild is an AI-powered resume builder that helps users create professional resumes, cover letters, and resignation letters. It offers a variety of features, including AI-powered resume writing, keyword targeting, real-time content analysis, and resume scoring. ResumeBuild is trusted by over 1.4 million users and has been featured in Forbes, The New York Times, and The Wall Street Journal.

Commit is a professional network for startup engineers. It features an AI Talent Agent that helps users find and apply to jobs that fit their developer profile. The platform also provides a community for users to connect with other engineers and collaborate on projects.

Pollinations.AI is an AI-powered platform that helps businesses find and hire the best talent. It uses machine learning to match candidates with jobs, and it provides a suite of tools to help businesses manage their hiring process.

HireList.io is an AI-driven recruitment software designed to streamline the hiring process for startups. It offers a range of features to help businesses target the right talent, connect with the right candidates, and build their dream team quickly and efficiently. HireList's AI-powered candidate filter narrows down the pool of applicants, highlighting only those who fit the bill. The platform also provides a streamlined hiring pipeline, taking businesses from job posting to welcoming their new hire. With HireList, businesses can create and tailor job postings, review and comment on candidates, and track their progress through the hiring process. The platform also offers communication automation, structured interviews, and performance tracking to help businesses refine their hiring practices.

Amabay is an AI agent application that assists users in handling queries by creating personalized bots. Users can easily generate their own 'Amabot' in less than 5 minutes, which can provide accurate and objective answers based on the user's information. The platform allows users to share their bots as spokespersons, answer worldwide questions, find job opportunities, and showcase themselves anonymously through AMAs. Amabay offers a new way to connect with others and discover mutual interests through AI-powered technology.

The WhatsApp AI Assistant repository offers a chatbot named Sydney that serves as an AI-powered personal assistant. It utilizes Language Model (LLM) technology to provide various features such as Google/Bing searching, Google Calendar integration, communication capabilities, group chat compatibility, voice message support, basic text reminders, image recognition, and more. Users can interact with Sydney through natural language queries and voice messages. The chatbot can transcribe voice messages using either the Whisper API or a local method. Additionally, Sydney can be used in group chats by mentioning her username or replying to her last message. The repository welcomes contributions in the form of issue reports, pull requests, and requests for new tools. The creators of the project, Veigamann and Luisotee, are open to job opportunities and can be contacted through their GitHub profiles.

The Linkedin API for Python allows users to programmatically search profiles, send messages, and find jobs using a regular Linkedin user account. It does not require 'official' API access, just a valid Linkedin account. However, it is important to note that this library is not officially supported by LinkedIn and using it may violate LinkedIn's Terms of Service. Users can authenticate using any Linkedin account credentials and access features like getting profiles, profile contact info, and connections. The library also provides commercial alternatives for extracting data, scraping public profiles, and accessing a full LinkedIn API. It is not endorsed or supported by LinkedIn and is intended for educational purposes and personal use only.

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

The Mistral JavaScript client is a library that allows you to interact with the Mistral AI API. With this client, you can perform various tasks such as listing models, chatting with streaming, chatting without streaming, and generating embeddings. To use the client, you can install it in your project using npm and then set up the client with your API key. Once the client is set up, you can use it to perform the desired tasks. For example, you can use the client to chat with a model by providing a list of messages. The client will then return the response from the model. You can also use the client to generate embeddings for a given input. The embeddings can then be used for various downstream tasks such as clustering or classification.

runpod-worker-comfy is a serverless API tool that allows users to run any ComfyUI workflow to generate an image. Users can provide input images as base64-encoded strings, and the generated image can be returned as a base64-encoded string or uploaded to AWS S3. The tool is built on Ubuntu + NVIDIA CUDA and provides features like built-in checkpoints and VAE models. Users can configure environment variables to upload images to AWS S3 and interact with the RunPod API to generate images. The tool also supports local testing and deployment to Docker hub using Github Actions.

Extractor is an AI-powered data extraction library for Laravel that leverages OpenAI's capabilities to effortlessly extract structured data from various sources, including images, PDFs, and emails. It features a convenient wrapper around OpenAI Chat and Completion endpoints, supports multiple input formats, includes a flexible Field Extractor for arbitrary data extraction, and integrates with Textract for OCR functionality. Extractor utilizes JSON Mode from the latest GPT-3.5 and GPT-4 models, providing accurate and efficient data extraction.

llm-finetuning is a repository that provides a serverless twist to the popular axolotl fine-tuning library using Modal's serverless infrastructure. It allows users to quickly fine-tune any LLM model with state-of-the-art optimizations like Deepspeed ZeRO, LoRA adapters, Flash attention, and Gradient checkpointing. The repository simplifies the fine-tuning process by not exposing all CLI arguments, instead allowing users to specify options in a config file. It supports efficient training and scaling across multiple GPUs, making it suitable for production-ready fine-tuning jobs.

Yet Another Applied LLM Benchmark is a collection of diverse tests designed to evaluate the capabilities of language models in performing real-world tasks. The benchmark includes tests such as converting code, decompiling bytecode, explaining minified JavaScript, identifying encoding formats, writing parsers, and generating SQL queries. It features a dataflow domain-specific language for easily adding new tests and has nearly 100 tests based on actual scenarios encountered when working with language models. The benchmark aims to assess whether models can effectively handle tasks that users genuinely care about.

AI Town is a virtual town where AI characters live, chat, and socialize. This project provides a deployable starter kit for building and customizing your own version of AI Town. It features a game engine, database, vector search, auth, text model, deployment, pixel art generation, background music generation, and local inference. You can customize your own simulation by creating characters and stories, updating spritesheets, changing the background, and modifying the background music.

Mobius is an AI infra platform including realtime computing and training. It is built on Ray, a distributed computing framework, and provides a number of features that make it well-suited for online machine learning tasks. These features include: * **Cross Language**: Mobius can run in multiple languages (only Python and Java are supported currently) with high efficiency. You can implement your operator in different languages and run them in one job. * **Single Node Failover**: Mobius has a special failover mechanism that only needs to rollback the failed node itself, in most cases, to recover the job. This is a huge benefit if your job is sensitive about failure recovery time. * **AutoScaling**: Mobius can generate a new graph with different configurations in runtime without stopping the job. * **Fusion Training**: Mobius can combine TensorFlow/Pytorch and streaming, then building an e2e online machine learning pipeline. Mobius is still under development, but it has already been used to power a number of real-world applications, including: * A real-time recommendation system for a major e-commerce company * A fraud detection system for a large financial institution * A personalized news feed for a major news organization If you are interested in using Mobius for your own online machine learning projects, you can find more information in the documentation.

X-Hiring is a job search tool that uses Google AI to extract summaries of the latest job postings. It is easy to install and run, and can be used to find jobs in a variety of fields. X-Hiring is also open source, so you can contribute to its development or create your own custom version.

LinkedIn_AIHawk is an automated tool designed to revolutionize the job search and application process on LinkedIn. It leverages automation and artificial intelligence to efficiently apply to relevant positions, personalize responses, manage application volume, filter listings, generate dynamic resumes, and handle sensitive information securely. The tool aims to save time, increase application relevance, and enhance job search effectiveness in today's competitive landscape.

Auto_Jobs_Applier_AIHawk is an AI-powered job search assistant that revolutionizes the job search and application process. It automates application submissions, provides personalized recommendations, and enhances the chances of landing a dream job. The tool offers features like intelligent job search automation, rapid application submission, AI-powered personalization, volume management with quality, intelligent filtering, dynamic resume generation, and secure data handling. It aims to address the challenges of modern job hunting by saving time, increasing efficiency, and improving application quality.

DeepSeek is a new experimental architecture for a large language model (LLM) powered internet-scale retrieval engine. Unlike current research agents designed as answer engines, DeepSeek aims to process a vast amount of sources to collect a comprehensive list of entities and enrich them with additional relevant data. The end result is a table with retrieved entities and enriched columns, providing a comprehensive overview of the topic. DeepSeek utilizes both standard keyword search and neural search to find relevant content, and employs an LLM to extract specific entities and their associated contents. It also includes a smaller answer agent to enrich the retrieved data, ensuring thoroughness. DeepSeek has the potential to revolutionize research and information gathering by providing a comprehensive and structured way to access information from the vastness of the internet.

ResumeFlow is an automated system utilizing Large Language Models (LLMs) to streamline the job application process. It aims to reduce human effort in various steps of job hunting by integrating LLM technology. Users can access ResumeFlow as a web tool, install it as a Python package, or download the source code. The project focuses on leveraging LLMs to automate tasks such as resume generation and refinement, making job applications smoother and more efficient.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

This simple package can be used to fix an invalid json string. To know all cases in which this package will work, check out the unit test. Inspired by https://github.com/josdejong/jsonrepair Motivation Some LLMs are a bit iffy when it comes to returning well formed JSON data, sometimes they skip a parentheses and sometimes they add some words in it, because that's what an LLM does. Luckily, the mistakes LLMs make are simple enough to be fixed without destroying the content. I searched for a lightweight python package that was able to reliably fix this problem but couldn't find any. So I wrote one How to use from json_repair import repair_json good_json_string = repair_json(bad_json_string) # If the string was super broken this will return an empty string You can use this library to completely replace `json.loads()`: import json_repair decoded_object = json_repair.loads(json_string) or just import json_repair decoded_object = json_repair.repair_json(json_string, return_objects=True) Read json from a file or file descriptor JSON repair provides also a drop-in replacement for `json.load()`: import json_repair try: file_descriptor = open(fname, 'rb') except OSError: ... with file_descriptor: decoded_object = json_repair.load(file_descriptor) and another method to read from a file: import json_repair try: decoded_object = json_repair.from_file(json_file) except OSError: ... except IOError: ... Keep in mind that the library will not catch any IO-related exception and those will need to be managed by you Performance considerations If you find this library too slow because is using `json.loads()` you can skip that by passing `skip_json_loads=True` to `repair_json`. Like: from json_repair import repair_json good_json_string = repair_json(bad_json_string, skip_json_loads=True) I made a choice of not using any fast json library to avoid having any external dependency, so that anybody can use it regardless of their stack. Some rules of thumb to use: - Setting `return_objects=True` will always be faster because the parser returns an object already and it doesn't have serialize that object to JSON - `skip_json_loads` is faster only if you 100% know that the string is not a valid JSON - If you are having issues with escaping pass the string as **raw** string like: `r"string with escaping\"" Adding to requirements Please pin this library only on the major version! We use TDD and strict semantic versioning, there will be frequent updates and no breaking changes in minor and patch versions. To ensure that you only pin the major version of this library in your `requirements.txt`, specify the package name followed by the major version and a wildcard for minor and patch versions. For example: json_repair==0.* In this example, any version that starts with `0.` will be acceptable, allowing for updates on minor and patch versions. How it works This module will parse the JSON file following the BNF definition: ::= | ::= | | ; Where: ; is a valid real number expressed in one of a number of given formats ; is a string of valid characters enclosed in quotes ; is one of the literal strings 'true', 'false', or 'null' (unquoted) ::=