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Recently Added Machine Learning Engineers in our Network

Pranit Abhinav

Pranit AbhinavProfile Badge IC

Machine Learning Engineer (Computer Vision)4 Years of Exp
  • Python
  • NLP
  • PyTorch
  • TensorFlow
  • Flask
  • Computer Vision
  • ANN
  • AWS
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I am a motivated and inquisitive machine learning engineer with 5 years of experience in building and optimizing distributed machine learning systems for model training and inference.

Sai Vignan Malyala

Sai Vignan MalyalaProfile Badge IC

Head LLM Engineer - Gen AI Architect10.4 Years of Exp
  • machine_learning
  • data-science
  • Cloud DevOps
  • DevOps
  • Deep Learning
  • View all (7)

Principal Data Scientist/ Head of AI / Mentor with vast experience in building AI use-cases from scratch and deploying them to production. Amazing experience in GenAi, LLm fine-tuning , RAG, vector databases, NLP, Machine learning, Deep learning, transfer learning, working with LLM, MLOPS, deployment using aws, airflow, data bricks, pyspark, pipelining, containerization. Effective and proactive communicator with experience in leading teams and projects. Expertise in Computer Vision for OCR related information extraction from images, pdf parser, XML parser, box detection, entity detection and recognition, Data Mining, Data tagging, Data Analysis, Feature Selection & Model Selection, Model Building, Model Validation, Model threshold validation, log analysis.

Gelli Tarun

Gelli TarunProfile Badge IC

Data Scientist4.3 Years of Exp

A skilled machine learning engineer passionate about solving real-world problems. Wish to explore this cutting-edge technology to help organizations develop new and integrate products Collaborated with multivariate teams of product development to insert trained models and gauge performance improvement. Planned, researched, and developed SOTA deep learning models to evaluate and perform semantic segmentation, object detection, and classifications. Developed data analysis and data preparation pipeline.

Abhay Kansal

Abhay KansalProfile Badge IC

Senior Engineering Manager ML/AI12.7 Years of Exp

A resultsdriven AI/ML Leader with over 12 years of experience driving impactful solutions for complex, greenfield challenges across diverse sectors including Nuclear, Automotive, IoT, and Health. Passionate about building highperforming teams and strategically driving innovation to achieve key business objectives.

Amith K A

Amith K AProfile Badge IC

Head of AI & Engineering17 Years of Exp
  • machine_learning
  • Deep Learning
  • Azure
  • SAS
  • System Design
  • View all (7)

Amith KA is a seasoned professional with 14.5 years of expertise in leadership, management, and a comprehensive skill set spanning data engineering, data science, and systems design. Proficient in engineering best practices, data architecture, and cloud platforms such as GCP, AWS, and AZURE, Amith excels in full-stack development and employs tools like Terraform for efficient infrastructure management. With proficiency in Python, TensorFlow, PyTorch, and BigQuery, Amith is a specialist in machine learning, deep learning, MLOPS, and Kubernetes. Additionally, expertise in areas like NLP, computer vision, and generative AI, along with a strong background in security and Docker, further underscores Amith's impact in the industry.

Shantanu Sharma

Shantanu SharmaProfile Badge IC

Senior AI/ML engineer7 Years of Exp
  • JavaScript
  • Java
  • Python
  • machine_learning
  • SQL
  • PyTorch
  • TensorFlow
  • View all (10)

I am a passionate programmer, dedicated learner, and experienced data scientist with a deep love for solving complex problems through data-driven approaches. My enthusiasm for exploring and implementing diverse algorithms has driven me to continually expand my expertise and tackle a variety of challenging, real-world issues.Currently, I am working as a Senior Data Scientist, where I develop innovative and optimized solutions for the healthcare industry. My work involves leveraging deep learning, reinforcement learning, natural language processing (NLP), and large language models (LLMs) to create impactful and efficient outcomes.Let's connect and explore how we can collaborate to drive data science initiatives forward!

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Uplers earned our trust by listening to our problems and finding the perfect talent for our organization.

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Uplers helped to source and bring out the top talent in India, any kind of high-level role requirement in terms of skills is always sourced based on the job description we share. The profiles of highly vetted experts were received within a couple of days. It has been credible in terms of scaling our team out of India.

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Uplers efficient, quick process and targeted approach helped us find the right talents quickly. The professionals they provided were not only skilled but also a great fit for our team.

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Uplers' talents consistently deliver high-quality work along with unmatched reliability, work ethic, and dedication to the job.

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Case Studies of Tech Companies

Check Our Latest Blogs

Machine Learning Engineer Hiring Trends: What You Need to Know

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.

Common Mistakes to Avoid When Hiring 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.

What are the Essential Skills and Responsibilities required to hire Machine Learning Engineers

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.

Key Capabilities of Machine Learning Engineers Powering Smart Systems

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.

Frequently Asked Questions

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:

  • Email
  • Phone
  • Messaging apps such as WhatsApp, Slack, or Microsoft Teams

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.

View Our Pricing For 2025 - 26

Yes, ML engineers have a proliferating demand due to the rising adoption of machine learning technologies across various industries.