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Machine Learning is one of those technologies that has taken the tech market by a turmoil. Businesses are recognizing the value of AI-driven insights and automation resulting in the skyrocketing demand for machine learning engineers.
As a business looking to leverage data-driven solutions to hire machine learning engineers is non-negotiable. The rapidly evolving nature of machine learning can be challenging, which is why hiring managers need to be on point of the common pitfalls that can result in poor hiring decisions.
Technological advancements have taken the industry by a revolution where Artificial Intelligence and Machine Learning have taken over. Machine learning engineers have a pivotal role to play in developing systems and algorithms that enable machines to learn from data and perform tasks without the traditional human intervention.
Building smart systems is not merely about having data, it's about having the right team of developers to make sense of it. This starts with knowing how to hire and for product companies the demand to hire machine learning engineers has grown beyond buzzwords.
We provide mid to senior-level machine learning engineers with experience across supervised, unsupervised, and reinforcement learning. They are proficient in Python, TensorFlow, PyTorch, Scikit-learn, and can work on models involving predictive analytics, NLP, and computer vision.
Yes. Whether you're building an internal tool, working on a client-facing product, or need support for consulting assignments, our ML engineers can seamlessly integrate into your workflow.
Yes, our engineers are remote-ready and can work in sync with US, UK, EU, or APAC time zones, depending on your team's schedule.
We typically share vetted profiles within 48 hours. You can expect candidates who match your JD and are ready for interviews almost immediately.
No. We maintain a pool of pre-vetted, actively available talent. Most are either in their notice period or looking for immediate engagement, and are ready to onboard after your selection.
Absolutely. Whether you're hiring for a short-term AI use case or need a long-term engineer embedded in your product team, we offer both contract and full-time engagement options.
Our pricing starts at $2,500/month, varying with experience level and complexity of the role. We offer flexible engagement terms tailored to your needs.
We offer a lifetime replacement guarantee. If the hired talent doesn't meet expectations, we'll help you find a better fit, no hassle.
Yes. Many of our engineers have worked on end-to-end ML lifecycle tasks, data prep, model training, validation, and deploying models using MLOps tools on cloud platforms like AWS, Azure, or GCP.
Yes. If you're scaling your AI function, we can help you onboard multiple machine learning engineers or even cross-functional teams (including data engineers, backend developers, and analysts) as per your roadmap.
The modes of communication through which you can get in touch with a hired machine learning engineers include:
The average cost of hiring a Machine Learning engineer from Uplers starts at $2500. The number varies depending on the experience level of the developer as well as your requirements.
Yes, ML engineers have a proliferating demand due to the rising adoption of machine learning technologies across various industries.
