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Vetted Deep Reinforcement Learning developer in Romania (UTC+3)
I am a passionate data scientist with several years of experience in the industry, having previously graduated from Queen Mary University of London with a MSc. in Big Data Science. My specialty is deep learning, with a focus on natural language processing (NLP). I am a Microsoft Certified Azure AI Engineer and additionally I have successfully completed a 6-month deep learning specialization offered by leading AI engineer Andrew Ng. I have a CS background and I am constantly increasing my theoretical understanding of ML techniques and computing environments.
IBM
Deep Reinforcement Learning developer in Poland (UTC+1)
As a highly skilled and experienced professional with a Master’s degree in Liberal Arts in Data Science, I excel in data-driven decision-making. With expertise in automation of data acquisition, data analysis, predictive models, image analysis/classification, and language models, I am well-versed in harnessing the power of big data to drive strategic insights and outcomes. My passion for data flows through my veins, and my keen eye for numbers allows me to decipher complex patterns and trends and provide context and support for your informed decisions. As a specialist in difficult matters, I thrive in challenging situations and possess a proven track record of solving complex problems efficiently. I believe in the value of active listening, ensuring that I fully understand the nuances of any situation before offering strategic solutions. My expertise in leveraging cutting-edge technologies, deep understanding of data-driven decision-making, and education from the Faculty of Arts and Sciences of Harvard University make me a valuable asset in any business environment.
Deep Reinforcement Learning developer in China (UTC+8)
15 years of experience in machine vision, image algorithms, and deeplearning,specializinginroboticvisionanddefectdetection. AlgorithmLeadatasurgicalroboticscompanywithdeepexpertise infoundationaltechnologies. Proficient in mainstream algorithms and network architectures, achievingexcellentresultsinvariousvisionprocessingprojects.
Vetted Deep Reinforcement Learning developer in the United States (UTC-5)
Howdy! I'm Rob and I solve problems. ✅ I am a startup founder and entrepreneur, career long startup technical leader (early employee at Twilio, Boxee and many others) and full stack developer with 15 years of Python, the last 7 of which in machine learning and artificial intelligence. My favorite problems are short term, high impact challenges that yield new valuable insight, automate the previously impossible or transform your customer's success. As a racing driver, I love bringing urgency and speed to all adventures on and off track. Skills and Experience: 🤖 Extensive production use of state-of-the-art large language models (LLMs) like GPT-4o/o1/o3-mini, Gemini Flash 2.0, DeepSeek R1, Llama 3, Claude 3.5 Sonnet/Opus, Mistral, and Qwen. 👷 Deployed AI projects with frameworks like LangChain, LlamaIndex, Claude Computer Use 🗿 Custom modeling using training, fine tuning, reinforcement learning, Hive, Scale, Databricks and more 🤹 Multi-agent solutions with Claude Computer Use, CrewAI, Agno, OpenAI Swarm and LangGraph 📡 Data collection and web scraping in adversarial conditions using Scrapy, AgentQL, BrowserBase, captcha solving, bot evasion 👀 Proven computer vision experience with OpenCV, YOLO, Stable Diffusion, Flux and more 💰 Driven significant reduction in token consumption, training and inference compute with fine tuning, quantization, Langtrace, Unsloth, OpenRouter, and NotDiamond 🎱 Discovering new insights with data visualization, matplotlib, SeaBorn, D3, billboard.js, 🚚 Delivering full stack production software with Python, Vue 3, JavaScript / TypeScript, Next.js, Nuxt.js, Tailwind, and more 📼 Production experience with Postgres, MySQL, Pinecone, LanceDB, MongoDB, BigQuery, DynamoDB, Firebase, Snowflake, or Clickhouse 📞 Deep experience in voice platforms Twilio, Vonage, AssemblyAI, ElevenLabs, and Gemini Realtime ☁ Deploy to AWS, GCP, Azure, DigitalOcean, Linode, or rack and stack your own gear Achievements: 🔔 Took Twilio's developer GTM from 13k developers to 1.7 million - Series A to ringing the bell at the NYSE 🏆 Transitioned Darpa Memex project Tellfinder with District Attorney of New York 🤑 CTO of first startup (BZ Results) acquired by ADP for $125M ⚾ Earned $3.9k with custom fantasy baseball bot Community: 🎤 Speaker at dozens of conferences internationally, US, UK, CA, France, Germany, Czech Republic, Spain, Ireland, Portugal, China, India 💻 Multiple hackathon winner and organizer like Music Hack Day, Game Hack Day, TechCrunch Disrupt, and more 🏁 Autocross and spec Miata driver, driver in first team to cross the United States in under 24 hours Let's prototype fast, iterate quickly and ship solutions now. What problem are you trying to solve?
Twilio
Vetted Deep Reinforcement Learning developer in the United States (UTC-7)
*****General profile***** Hello! ex-Amazon engineer here. I have 5+ yoe in fullstack development and 1.5 yoe in AI engineering (JS and Python) I have both worked at startups building products from the ground up and big tech building large-scale distributed systems. With my unique blend of fullstack and AI expertise, I'm confident I can bring your next product to success! *****Tutor profile***** As an ex-Amazon engineer, I came from a non-CS background and eventually broke into big tech. I have also conducted numerous interviews at Amazon, so I know the secret to cracking the coding interviews. With a solid coverage of DSA fundamentals and uniquely curated list of questions from past FAANG interviews, many of my students were able to land jobs at FAANG companies. So whether you are a student or a seasoned engineer, I'm happy to help you land your next dream school/job! I'm currently an independent AI researcher offering tutoring with a part-time capacity at a discounted rate! Therefore, this opportunity may not be long! *****Tech stacks***** Proficient in Python, JavaScript, React, Vue.js, MySQL, PostgreSQL, MongoDB, PyTorch, Scikit-Learn, AutoML,OpenAI, LLM, Langchain, RAG. Look forward to collaborating with you!
Vetted Deep Reinforcement Learning developer in the United States (UTC-5)
I am an experienced ML/AI/DL Engineer with a strong foundation in data analysis, machine learning, and predictive modeling, specializing in extracting insights from large, complex datasets using advanced tools like Python, Spark MLlib, and SQL. I have a passion for solving business problems through data-driven solutions, with expertise in NLP, deep learning, and model optimization. Looking ahead, my career aspirations involve further exploring AI-driven innovations and contributing to impactful projects, particularly in machine learning and AI applications, while advancing my skills in cloud technologies like AWS and Azure for scalable model deployment.
Deep Reinforcement Learning developer in India (UTC-8)
Hi, I’m **Aayush Agrawal**, a **Lead Machine Learning Engineer** with **7+ years of experience** developing innovative solutions in **NLP/LLMs**, **reinforcement learning**, and **computer vision**. I thrive on building scalable machine learning models to solve real-world challenges across industries like **EdTech**, **transportation**, and **FMCG**. **What I Do** * **NLP & LLMs**: Built multi-task NLP models (summarization, Q&A) using **LoRA** to optimize massive 11B-parameter models. Created a grammar correction model trained on **40M+ data points**. * **Optimization & Efficiency**: Reduced logistics costs by **15%** (~1M INR/day) with RL-based LineHaul solutions. Delivered shrinkage detection for retail using **YOLOv5** and SORT algorithms. * **AI Solutions**: Developed **TinyLlama** to classify academic answers, a chatbot using **LangChain**, and speech-to-text models with a WER of **9%**. **Skills** I specialize in **Python**, **TensorFlow**, **PyTorch**, **Docker**, **Kubernetes**, and cloud platforms like **AWS** and **GCP**. I’m passionate about creating seamless, end-to-end ML pipelines that make an impact. **Let’s Connect** If you're looking for someone to design, build, and deploy cutting-edge ML solutions, let’s connect!
Vetted Deep Reinforcement Learning developer in the United States (UTC-4)
My summary is as follows: \- 7 years in team management including 5-70 members of teams including top-level managers \- Excellent track record of bridging the gap between technical teams & executives and the ability to translate business initiatives into technical requirements. \- 6 years as a Professional Data scientist including senior level, team lead, and chief data scientist \- 5 years of consultancy to provide visibility and insights into key business issues. \- 6 years in Business Analytic Projects (customer journey, customer target selection, online pricing, target selection, recommendation engine). \- 5 years of experience with Extract Intelligence from Data using Data Preprocessing, EDA (Explorative Data Analysis) \- 7 years of deep theoretical and practical knowledge of Machine Learning (ML) Algorithms \- 12 years of Solid Experience in Computer Vision (CV) (object detection, Background / Foreground Subtraction, Object verification, Counting objects). \- 11 years in Research and Development (R&D) including e-commerce, defense, finance, and telecommunication industry. \- 10 years in Software Programming as a Professional developing algorithm (C, C++, Python, MATLAB) \- 6 years of experience in Deep Learning (DL) using FRCNN, InceptionV3, and CNN mask architecture for Computer vision projects. \- 3 years of Sequential Modelling using DL based approach (LSTM, GRU), Statistical Approach (Arima, Sarima), and Graph-Based approach (Markov chain, finite state space modeling) for (NLP, sales forecasting) \- 4 years in Time serial analysis from data processing (lead, lag insertion using auto-correlation analysis) to developing models (with evaluation by comparing persistence model, moving average model, and Gaussian smoothing) \- 6 years of fluent Tensor Flow, Keras, pandas, and scikit-learn experience \- 4 years of experience in Agile development methodologies with emphasis on Scrum. \- 1-year experience in Reinforcement Learning using DQN (Deep Q Network), cross-entropy method with MLP \- 3 years in Machine Learning (ML) applications for Wireless Communications: Signal Detection, Channel Estimation, Channel Encoding-Decoding, and Resource Allocation. \- 4 years in Big Data, Cloud Computing, and NoSQL Databases \- Excellent record of accomplishment in defining, designing, developing, and implementing phenomenally successful automated and deployed solutions. \- Strong interpersonal, written, and verbal communicator who can deliver effective presentations and maintain collaborative relationships. Muhammet Pakyurek +1(319)259-3907 mpak85@hotmail.com
Vetted Deep Reinforcement Learning developer in Canada (UTC-8)
Senior Full Stack Developer with 10+ years of experience in scalable applications, specializing in cloud-based infrastructures. Skilled in delivering high-quality features with TypeScript, JavaScript, React, Next.js, and Node.js. Proven expertise in designing and implementing RESTful APIs and microservices, and mentoring engineering teams to foster best practices and technical excellence.
Deep Reinforcement Learning developer in Dominican Republic (UTC-4)
I have extensive experience in quantitative mI’m a Data Scientist and Machine Learning Engineer working in multiple applications and getting the best insights out of data, the 21st Century gold. I enjoy turning complex problems into simple, practical, innovative, and impactful solutions. My job is to create end-to-end Machine Learning products alongside performing hands-on data analyses over enormous datasets toward detecting patterns and inducing better data-driven decision making. With over 6 years of industry experience, I have applied quantitative analysis, experiment design, and develop machine learning models for diverse business solutions. Throughout this experience, I have had the opportunity to design and create models that are helping organizations manage risk behavior profiles, reduce tax gaps, and build advanced analytical engines for forecasting and detecting deviations from unstructured information., and conducted exploratory variable research.
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FAQs
Why hire a Deep Reinforcement Learning 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 Deep Reinforcement Learning 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 Deep Reinforcement Learning developers can help keep your website up-to-date.
How do I hire Deep Reinforcement Learning developers?
To hire a Deep Reinforcement Learning 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 Deep Reinforcement Learning developers effectively and efficiently. Hire full-time Deep Reinforcement Learning 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 Deep Reinforcement Learning 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 Deep Reinforcement Learning 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 Deep Reinforcement Learning developers for your company, and let Arc handle the logistics.
Where do I hire the best remote Deep Reinforcement Learning developers?
There are two types of platforms you can hire Deep Reinforcement Learning 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 Deep Reinforcement Learning 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 Deep Reinforcement Learning developers, consider niche platforms like Arc that naturally attract and carefully vet their Deep Reinforcement Learning developers for hire. This way, you’ll save time and related hiring costs by only interviewing the most suitable remote Deep Reinforcement Learning developers.
Some factors to consider when you hire Deep Reinforcement Learning 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 Deep Reinforcement Learning developers for hire.
How do I write a Deep Reinforcement Learning developer job description?
Writing a good Deep Reinforcement Learning developer job description is crucial in helping you hire Deep Reinforcement Learning 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 Deep Reinforcement Learning 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 Deep Reinforcement Learning developers, read our Engineer Job Description Guide & Templates.
What skills should I look for in a Deep Reinforcement Learning developer?
The top five technical skills Deep Reinforcement Learning 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 Deep Reinforcement Learning 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 Deep Reinforcement Learning developers to keep up with evolving technology and requirements.
What kinds of Deep Reinforcement Learning developers are available for hire through Arc?
You can find a variety of Deep Reinforcement Learning developers for hire on Arc! At Arc, you can hire on a freelance, full-time, part-time, or contract-to-hire basis. For freelance Deep Reinforcement Learning developers, Arc matches you with the right senior developer in roughly 72 hours. As for full-time remote Deep Reinforcement Learning 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 Deep Reinforcement Learning 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 Deep Reinforcement Learning developers?
Arc is trusted by hundreds of startups and tech companies around the world, and we’ve matched thousands of skilled Deep Reinforcement Learning developers with both freelance and full-time jobs. We’ve successfully helped Silicon Valley startups and larger tech companies like Spotify and Automattic hire Deep Reinforcement Learning developers.
Every Deep Reinforcement Learning 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 Deep Reinforcement Learning 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 Deep Reinforcement Learning developer's skills?
Arc has a rigorous and transparent vetting process for all types of developers. To become a vetted Deep Reinforcement Learning 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 Deep Reinforcement Learning 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 Deep Reinforcement Learning developers, you can rest assured that all remote Deep Reinforcement Learning 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 Deep Reinforcement Learning developers on Arc?
Arc pre-screens all of our remote Deep Reinforcement Learning developers before we present them to you. As such, all the remote Deep Reinforcement Learning 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 Deep Reinforcement Learning developer in 72 hours, or find a full-time Deep Reinforcement Learning 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 Deep Reinforcement Learning developers.
How much does a freelance Deep Reinforcement Learning developer charge per hour?
Depending on the freelance developer job board you use, freelance remote Deep Reinforcement Learning developers' hourly rates can vary drastically. For instance, if you're looking on general marketplaces like Upwork and Fiverr, you can find Deep Reinforcement Learning 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 Deep Reinforcement Learning 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 Deep Reinforcement Learning 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 Deep Reinforcement Learning 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 Deep Reinforcement Learning developers, check out our FAQs page.