Innovyq Solutions
About
At Innovyq Solutions, we're transforming the way businesses find and hire top talent. We harness the power of artificial intelligence and machine learning to streamline every stage of the recruitment lifecycle, from intelligent sourcing to unbiased candidate assessment and seamless onboarding. Our mission is to empower organizations to build exceptional teams by connecting them with the right people, faster and more accurately than ever before.
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IT Recruitment
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Jobs at Innovyq Solutions
About the Role:
We are seeking an experienced AI Engineer to design, develop, and deploy advanced artificial intelligence solutions. The ideal candidate has strong expertise in machine learning, deep learning, and data-driven problem-solving, with a proven track record of delivering scalable AI applications.
Key Responsibilities:
- Design, build, and optimize AI/ML models for production use cases, ensuring scalability and performance.
- Work with large-scale datasets: data collection, cleaning, preprocessing, and feature engineering.
- Implement deep learning architectures (CNNs, RNNs, Transformers) for NLP, computer vision, or other domains as required.
- Integrate AI solutions into existing software products via APIs or embedded models.
- Conduct model performance evaluation, optimization, and monitoring in production environments.
- Collaborate with cross-functional teams including data scientists, software engineers, and product managers.
- Stay updated with the latest research and advancements in AI/ML technologies and frameworks.
Required Skills & Qualifications:
- Bachelor’s/Master’s in Computer Science, Artificial Intelligence, Data Science, or related field.
- 4+ years of hands-on experience in AI/ML development and deployment.
- Proficiency in Python and AI/ML libraries such as TensorFlow, PyTorch, scikit-learn, Hugging Face, etc.
- Strong understanding of machine learning algorithms, model optimization, and evaluation metrics.
- Experience with cloud platforms (AWS, Azure, GCP) for AI/ML workloads.
- Familiarity with MLOps practices, CI/CD pipelines, and containerization (Docker, Kubernetes).
- Excellent problem-solving skills and ability to translate business problems into technical solutions.
Preferred Qualifications:
- Experience with LLM fine-tuning, prompt engineering, or generative AI applications.
- Exposure to reinforcement learning or graph neural networks.
- Contributions to open-source AI projects or published research papers.
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