Hire the best freelance Recommender Systems developers
Arc helps you find and hire top freelance Recommender Systems engineers for
your jobs. With 2,632 Recommender Systems programmers available for hire on a
freelance basis, we have one of the largest network of vetted talent. Our
Silicon Valley-caliber vetting process helps ensure that you hire
freelance Recommender Systems developers and experts that you can trust.
Experienced machine learning engineer with 5 years of proven ability to develop impactful end-to-end solutions for complex business problems. Specialized in recommendation systems and natural language processing, with extensive experience in problem definition, data pipeline development, feature engineering, model developing and deployment. Skilled in cross-functional communication and collaboration to provide effective and scalable ML strategies that address business needs. Seeking a senior machine learning engineer role where I can apply my expertise to create innovative solutions.
Machine Learning Engineer with over 4 years of experience, happy to work in different industries that might make use of AI tools. I am passionate about what I am doing and my career goal is to work on projects that really bring an impact on the world around us.
Hi there! I can help you with: 💻 fix your code 📊 data analysis 🔎 statistical analysis for research 🔮 machine learning algorithms 🧠 artificial neural networks ➕ and more. Languages: python, R
* Experienced in leveraging AWS technologies (Lambda, EC2, Beanstalk, DynamoDB, RDS, EMR, S3, SQS, etc) and opensource technologies like Cassandra, RabbitMQ, etc to solve problems and develop solutions.
* I also have experience with various data science and quant libraries like numpy, pandas, scipy, quantlib, pinescript, etc.
* I am someone who is empathetic, patient but a go-getter who likes to learn by doing and hacking.
* I hold myself to high standards of a software professional. This means that I am committed to: write the best code I can produce in the scope of the project, accountability, responsiveness, and setting clear expectations.
Mechanical engineer with a strong academic background, holding a Bachelor's degree from Universidad de los Andes and a Master of Science in Computational Mechanics from the Technical University of Munich (TUM). Over 4 years of academical experience and 5 years of professional experience, also have seamlessly transitioned into the field of data science and machine learning, where have excelled in solving complex business problems and deploying innovative solutions in production environments. Expertise lies in leveraging cutting-edge libraries like TensorFlow, Pytorch, and Scikit-Learn to develop cognitive services. With a versatile skill set, brings to the table a wealth of experience in time series modelling, programming proficiency in Python, C++, Java, and Matlab, and a solid foundation in High-Performance Computing (HPC).
With a B.S. in Math and a M.S in Computer Science, plus over 10 years experience at large and small research companies, at my heart I am a research engineer. I absolutely love to learn, to tackle big problems one piece at a time within an overall vision that builds on small successes but is always looking out for the 0-1 shift that unlocks a whole new world of opportunity.
I have spent the past 3 years helping start a data team at one of the largest faith-based apps in the world (the YouVersion "Bible App"). It's been a great experience and gave me a chance to learn more about the business side of the organization.
But in my heart I am a research engineer, so I'm looking forward to getting back into real technical research and development. I would be honored to have the chance to discuss how and where my skills and interests might align with real problems that your organization is trying to solve; particularly problems that involve end users and how we can make their world better.
Experienced AI/ML Engineer with over 5 years of full-stack AI/ML solution development, specializing in Large Language Models (LLM), Generative AI, and GPT. Proficient in integrating state-of-the-art research into practical AI architectures successfully implemented LLM and Generative AI products in media and entertainment sectors. My leadership skills are demonstrated through guiding a team of five in AI/ML innovations, fostering a culture of continuous learning and innovation
§ **END-TO-END AI/ML SOLUTIONS:** Demonstrated proficiency in full-stack AI/ML development, with a comprehensive background in **_LLM, Generative AI, Computer Vision, NLP, MLOps, and data engineering_,**leading to the delivery of robust AI products and actionable solutions for complex business challenges.
§ **STRATEGIC AI LEADERSHIP:** As a team leader and mentor, **guided AI/ML teams in developing and executing visionary AI** strategies aligned with company goals. This includes **managing vendor relations, heading project teams, and fostering a culture of continuous innovation and learning.**
§ **AI RESEARCH AND DEVELOPMENT_:_** Adapted cutting-edge research into practical applications, significantly **enhancing AI architectures for business use cases.** Notably authored **award-winning research** papers on digital governance and developed predictive models for e-governance, earning recognition in national reports.
§ **Diverse AI Framework Proficiency:** Showcased versatility across multiple AI platforms and tools, including **TensorFlow, PyTorch, FastAPI, and various cloud services**. This also encompasses the deployment of machine learning models, **leveraging Docker, Kubeflow, and MLflow, and optimizing infrastructure for scalability**.
I am a Lead AI Engineer at [Virtualness.io](http://virtualness.io/), specializing in AI, NLP, and recommendersystems. I have experience in ML engineering, research, and development across various industries.
I am a data scientist who has experience working with burgeoning companies like Siam Makro, Glance (Inmobi Group), EpiFi, and Tata 1mg.
I also have worked with different companies e.g. InterviewBit, Dezyre, and, RateCity as a research data science consultant.
My Domain Expertise is in Fintech, Edtech, and Ecommerce where I have built: recommendation engines, time-series forecasting models, product data science, natural language processing, etc.
I have a bias for action, solution-oriented, and have a good track record in communicating with stakeholders and establishing credibility. My role involves deciphering heaps of data, analyzing it, churning out meaningful insights from the data, and assisting stakeholders to make data-driven decisions.
I have experience in developing end-to-end data science models helping companies move business metrics. I constantly learn new things and explore new realms of data science.
If you're looking for immediate online assistance from Recommender Systems experts, you can get Recommender Systems programming help within 6 minutes on Codementor.
Why choose Arc to hire freelance Recommender Systems developers
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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 Recommender Systems developer, multiple developers, 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 Recommender Systems developers can help keep your website up-to-date.
How do I hire Recommender Systems developers?
To hire a Recommender Systems 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 Recommender Systems developers effectively and efficiently. Hire full-time Recommender Systems 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 Recommender Systems engineers 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 350,000 developers around the world. With that said, the free plan will not give you access to pre-vetted Recommender Systems 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 Recommender Systems developer for your company, and let Arc handle the logistics.
Where do I hire the best remote Recommender Systems developers?
There are two types of platforms you can hire Recommender Systems programmers 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 Recommender Systems 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 Recommender Systems developers, consider niche platforms like Arc that naturally attract and carefully vet their Recommender Systems developers for hire. This way, you’ll save time and related hiring costs by only interviewing the most suitable remote Recommender Systems developer candidates.
Some factors to consider when you hire Recommender Systems 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 Recommender Systems developers for hire.
How do I write a Recommender Systems developer job description?
Writing a good Recommender Systems developer job description is crucial in helping you hire Recommender Systems programmers 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 Recommender Systems 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.
What skills should I look for in a Recommender Systems engineer?
The top five technical skills Recommender Systems developers should possess include proficiency in programming languages, understanding data structures and algorithms, experience with databases, familiarity with version control systems, and knowledge of software 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 Recommender Systems 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 Recommender Systems developers to keep up with evolving technology and requirements.
What kinds of Recommender Systems programmers are available for hire through Arc?
You can find a variety of Recommender Systems developers for hire on Arc! At Arc, you can hire on a freelance, full-time, part-time, or contract-to-hire basis. For freelance Recommender Systems programmers, Arc matches you with the right senior developer in roughly 72 hours. As for full-time remote Recommender Systems 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 software engineers in various different time zones and countries for you to choose from.
Lastly, our remote-ready Recommender Systems 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 Recommender Systems developers?
Arc is trusted by hundreds of startups and tech companies around the world, and we’ve matched thousands of skilled Recommender Systems developers with both freelance and full-time jobs. We’ve successfully helped Silicon Valley startups and larger tech companies like Spotify and Automattic hire Recommender Systems developers.
Every Recommender Systems developer for hire in our network goes through a vetting process to verify their communication abilities, remote work readiness, and technical skills (both for depth in Recommender Systems and breadth across the greater domain). 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 Recommender Systems engineer 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 developer’s Recommender Systems skills?
Arc has a rigorous and transparent vetting process for all types of developers. To become a vetted Recommender Systems 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 Recommender Systems 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 Recommender Systems developers, you can rest assured that all remote Recommender Systems 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 Recommender Systems developers on Arc?
Arc pre-screens all of our remote Recommender Systems developers before we present them to you. As such, all the remote Recommender Systems 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 350,000 candidates. You can also expect to hire a freelance Recommender Systems programmer in 72 hours, or find a full-time Recommender Systems programmer 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.”
How much does a freelance Recommender Systems developer charge per hour?
Depending on the freelance developer job board you use, freelance remote Recommender Systems developers' hourly rates can vary drastically. For instance, if you're looking on general marketplaces like Upwork and Fiverr, you can find Recommender Systems 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 Recommender Systems 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 Recommender Systems developer?
According to the U.S. Bureau of Labor Statistics, the medium annual wage for software 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 Recommender Systems 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 Recommender Systems developers, check out our FAQs page.
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Arc helps you build your team with our network of full-time and freelance software developers worldwide, spanning 190 countries. We assist you in assembling your ideal team of programmers in your preferred location and timezone.