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Vetted Llm inference tuning developer in Singapore (UTC+8)
A highly accomplished professional leader, mentor, and guide, renowned for establishing numerous Data Validation and Quality Assurance teams across diverse industry domains including Media Application, ECommerce/Retail, and Telecom. Building High-Performing Teams: Proven track record of building and leading Data Validation and Quality Assurance teams from the ground up across Media Applications, E-commerce, and Telecom. Successfully managed teams of up to 30 Data Analysts, Testers, and Automation professionals, driving quality and efficiency in complex, high-stakes environments. Driving Innovation in Search & Personalization: Led a team of Market Insight and Search Language Analysts for Apple Media Products, focusing on data annotation, judgment ratings, and auditing. Optimized search and personalization features through offline data validation, NLP, LLMs, and AI/ML algorithms using human-centered insights. Domain Expertise: Recognized expert in Search and Personalization for Digital Media Products, with a strong focus on Human Factors and Trust & Safety. Extensive experience in Software Quality Assurance across E-commerce, Digital Publishing, Payments, and Telecom, ensuring optimal user experiences and system reliability. Agile Champion: Successfully implemented Agile methodologies to enhance team productivity and streamline testing processes during my tenures in DFS, SPH and Apple. Strategic Vendor Management: Proven ability to formulate effective vendor contracts (RFI/RFPs, MSAs, SOWs) alongside managing project budgets (CAPEX/OPEX) and overseeing invoicing processes. Exceptional People Leader: Demonstrated excellence in global team management, talent acquisition, performance & compensation planning, and mentoring large software and data validation teams.
Vetted Llm inference tuning developer in India (UTC+6)
Hi, I’m Lovish — a seasoned software developer and tech leader with 9 years of experience collaborating with startups and founders. I specialize in mobile development, AI, data analytics, product strategy, and team building. If you’re looking for a versatile expert who can code, lead, and deliver, let’s connect.
Vetted Llm inference tuning developer in Canada (UTC-6)
Experienced full-stack software engineer with a strong background in web development and competitive programming. Proficient in React.js, Next.js, GraphQL, and cloud technologies. Skilled in optimizing microservices architectures and delivering high-performance, scalable web applications. Combines problem-solving prowess with expertise in testing and DevOps practices.
Vetted Llm inference tuning developer in Bolivia (UTC-4)
I am a Machine Learning Engineer with experience in developing Machine Learning driven APIs using different backend frameworks and cloud technologies. I have expertise in Python, SQL, Cloud Technologies like AWS or Azure, and backend Frameworks and libraries like Django, FastAPI and Azure Durable Functions.
Llm inference tuning developer in the United States (UTC+2)
Hi, I’m **David Martín Rius**, a Senior Full-Stack Developer with a strong background in software development, artificial intelligence, and technical leadership. Currently, I work at **Proferox**, where I lead the selection and implementation of cutting-edge technologies, advising the CEO on the best tools to drive business growth. I have extensive experience with frameworks such as **Laravel, Django, React, Vue, and Next.js**, as well as expertise in **AI, machine learning, and automation**. My work spans **AI-powered applications, vector databases, NLP (TTS/STT), automated video generation, and serverless architectures**. Previously, I held roles as a **Technical Director and Senior Developer** at Fibracat, where I managed teams and led technical strategies. My journey also includes hands-on experience in **e-commerce development, mobile applications, and enterprise solutions** across multiple industries. I hold a **Bachelor’s Degree in Computer Engineering** from the Universitat Oberta de Catalunya and have a solid foundation in **computer systems administration**. I’m also multilingual, speaking **English, Spanish, Catalan, and with working knowledge of Chinese, Arabic, and Russian**.
Llm inference tuning developer in Pakistan (UTC-5)
**[Senior Machine Learning Engineer](https://www.linkedin.com/in/awais-amin-550693210)** Over 5 years of experience in designing and deploying AI/ML solutions, data science applications, and MLOps pipelines across diverse industries. * **Core Expertise**: Proficient in AI/ML and deep learning techniques, including Natural Language Processing (NLP), Computer Vision (CV), Generative AI (GenAI), Large Language Models (LLMs), Retrieval augmented generation (RAG), vector databases and Video/Image (Diffusion Models). * **Leadership and Execution**: Successfully led the end-to-end development of 4+ projects, from concept to deployment, working both individually and within cross-functional teams. * **Technical Proficiency**: Skilled in Object-Oriented Programming (OOP), unit testing, SDLC, CI/CD pipelines, Agile methodologies, and SOLID principles to ensure robust and scalable solutions.
Llm inference tuning developer in Brazil (UTC-4)
Fullstack Developer with 3+ years of experience building scalable web applications for national and international companies. Proficient in modern technologies like Angular, React, Node.js, NestJS, and Python. Recently involved in AI/LLM-based projects and cloud infrastructure (AWS, GCP). I thrive in remote, agile environments and aim to contribute to impactful tech products while continuously growing as a developer.
Llm inference tuning developer in the United States (UTC+9)
I’m a Technical Founder and Full Stack Engineer with 20+ years of experience building scalable SaaS platforms, leading cross-functional teams, and delivering AI-powered solutions. As Co-Founder & CTO of Haola Technology, I architected and launched health data systems used by over 50 insurance companies, serving millions of users. Recently, I led the development of an AI agent framework at a U.S. startup, integrating cutting-edge LLM techniques such as tool calling, RAG, and RLHF. My work spans industries including insurance, healthcare, energy, and telecom. I thrive on turning complex ideas into real-world systems that scale and deliver impact.
Llm inference tuning developer in India (UTC+6)
I am Ajith from Bangalore, India. I have completed my Master of Technology in Robotics and Automation from CET Trivandrum. Currently, I serve as a Research Engineer in a startup specializing in AI, where I have gained around 7 years of invaluable experience. I have prior research and development experience, both from the academia and the industry. Combining my academic background and research experience, I am confident in my abilities to contribute in research and help the industry to take a step forward towards a better solution. I am eager to discuss my qualifications in more detail and to learn more about the opportunity. Please feel free to contact me to set up a time to chat. I look forward to hearing from you. Thank you very much for your patience and consideration.
Llm inference tuning developer in North Macedonia (UTC+2)
Dedicated data science enthusiast with a background in Computer Science and Engineering, specializing in AI and Machine Learning. Skilled in collaborative and independent work, I prioritize high data quality. Committed to lifelong learning. Eager to connect with fellow professionals and explore new opportunities in data science and related fields. Let’s connect and drive innovation together!
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Ready to hire your ideal Llm inference tuning developers?
Get startedArc offers pre-vetted remote developers skilled in every programming language, framework, and technology. Look through our popular remote developer specializations below.
Arc helps you build your team with our network of full-time and freelance Llm inference tuning developers worldwide.
We assist you in assembling your ideal team of programmers in your preferred location and timezone.
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 Llm inference tuning 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 Llm inference tuning developers can help keep your website up-to-date.
To hire a Llm inference tuning 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 Llm inference tuning developers effectively and efficiently. Hire full-time Llm inference tuning 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 Llm inference tuning 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 Llm inference tuning 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 Llm inference tuning developers for your company, and let Arc handle the logistics.
There are two types of platforms you can hire Llm inference tuning 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 Llm inference tuning 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 Llm inference tuning developers, consider niche platforms like Arc that naturally attract and carefully vet their Llm inference tuning developers for hire. This way, you’ll save time and related hiring costs by only interviewing the most suitable remote Llm inference tuning developers.
Some factors to consider when you hire Llm inference tuning 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 Llm inference tuning developers for hire.
Writing a good Llm inference tuning developer job description is crucial in helping you hire Llm inference tuning 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 Llm inference tuning 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 Llm inference tuning developers, read our Engineer Job Description Guide & Templates.
The top five technical skills Llm inference tuning 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 Llm inference tuning 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 Llm inference tuning developers to keep up with evolving technology and requirements.
You can find a variety of Llm inference tuning developers for hire on Arc! At Arc, you can hire on a freelance, full-time, part-time, or contract-to-hire basis. For freelance Llm inference tuning developers, Arc matches you with the right senior developer in roughly 72 hours. As for full-time remote Llm inference tuning 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 Llm inference tuning developers for hire are all mid-level and senior-level professionals. They are ready to start coding straight away, anytime, anywhere.
Arc is trusted by hundreds of startups and tech companies around the world, and we’ve matched thousands of skilled Llm inference tuning developers with both freelance and full-time jobs. We’ve successfully helped Silicon Valley startups and larger tech companies like Spotify and Automattic hire Llm inference tuning developers.
Every Llm inference tuning 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 Llm inference tuning 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.
Arc has a rigorous and transparent vetting process for all types of developers. To become a vetted Llm inference tuning 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 Llm inference tuning 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 Llm inference tuning developers, you can rest assured that all remote Llm inference tuning developers have been thoroughly vetted for the high-caliber communication and technical skills you need in a successful hire.
Arc pre-screens all of our remote Llm inference tuning developers before we present them to you. As such, all the remote Llm inference tuning 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 Llm inference tuning developer in 72 hours, or find a full-time Llm inference tuning 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 Llm inference tuning developers.
Depending on the freelance developer job board you use, freelance remote Llm inference tuning developers' hourly rates can vary drastically. For instance, if you're looking on general marketplaces like Upwork and Fiverr, you can find Llm inference tuning 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 Llm inference tuning 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.
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 Llm inference tuning 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 Llm inference tuning developers, check out our FAQs page.