Senior AI Engineer
India - Remote
BlackStone eIT
Transform your business with our AI solutions. We offer machine learning, natural language processing, and computer vision to help you make data-driven decisions. Get in touch today to learn how our intelligent automation and predictive...We are seeking a highly skilled and experienced Senior AI Engineer to lead the design, development, and deployment of cutting-edge AI/ML solutions across our products and platforms. As a senior member of the team, you will be responsible for solving complex problems using AI technologies, mentoring junior engineers, and collaborating cross-functionally with product, data, and engineering teams to deliver scalable and impactful AI-driven features.
Key Responsibilities:
- Design and develop advanced machine learning models and deep learning architectures for real-world problems.
- Lead AI/ML system design, including data pipelines, model training workflows, evaluation strategies, and deployment frameworks.
- Conduct research and experimentation with new algorithms, tools, and technologies to enhance the company’s AI capabilities.
- Collaborate with product managers, data scientists, and software engineers to translate business requirements into AI solutions.
- Mentor and guide junior AI engineers and data scientists, fostering best practices in coding, experimentation, and model deployment.
- Optimize and monitor model performance in production, including addressing issues of bias, drift, and latency.
- Stay current with AI research, tools, and industry trends, and bring innovative ideas into the team.
- Contribute to technical strategy and help define the roadmap for AI initiatives.
Requirements
- Bachelor's or Master’s degree in Computer Science, Engineering, Mathematics, or a related field (Ph.D. preferred).
- 5+ years of experience in AI/ML engineering with a strong portfolio of production-level projects.
- Deep knowledge of machine learning and deep learning algorithms (e.g., CNNs, RNNs, Transformers, LLMs).
- Proficient in Python and libraries such as TensorFlow, PyTorch, Scikit-learn, and Hugging Face.
- Strong experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow) and cloud platforms (e.g., AWS, GCP, Azure).
- Experience in deploying and maintaining models in production at scale.
- Strong understanding of data structures, algorithms, and software engineering principles.
- Excellent problem-solving skills and communication abilities.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow Architecture AWS Azure Computer Science Data pipelines Deep Learning Engineering GCP Kubeflow LLMs Machine Learning Mathematics MLFlow ML models MLOps Model deployment Model training Pipelines Python PyTorch Research Scikit-learn TensorFlow Transformers
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