We are looking for a highly motivated and passionate Senior AI Engineer who thrives on solving complex problems using cutting-edge AI / ML technologies. In this role, you will design, develop, and deploy scalable AI / ML solutions that directly impact real-world applications. You will collaborate closely with data scientists, software developers, and product managers to bring AI-driven innovation into production environments.
Key Responsibilities :
- Design, build, train, and deploy machine learning (ML) and deep learning (DL) models for production use cases.
- Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) to ensure clean, high-quality input data for models.
- Collaborate with cross-functional teams (Data Science, Development, Product, Business) to identify opportunities where AI can deliver business impact.
- Integrate AI / ML models into production pipelines, APIs, and enterprise applications ensuring scalability, robustness, and performance.
- Evaluate and optimize models for accuracy, efficiency, and cost-effectiveness.
- Keep up-to-date with the latest advancements in AI / ML frameworks, research papers, and tools, and recommend their adoption where relevant.
- Contribute to setting best practices, coding standards, and model governance in the AI / ML team.
Required Skills & Qualifications :
Strong expertise in Python and experience with major ML / DL frameworks TensorFlow, PyTorch, Scikit-learn.Proficiency with data handling & manipulation libraries Pandas, NumPy.Solid understanding of data structures, algorithms, and problem-solving techniques.Minimum 3+ years of hands-on experience in designing and deploying AI / ML solutions.Knowledge or project experience in at least one specialized area such as :1. Natural Language Processing (NLP)
2. Computer Vision
3. Recommendation Systems
Strong analytical skills and ability to convert business requirements into technical AI solutions.Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or related field.Good to Have (Optional Skills) :
Experience with MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes).Familiarity with cloud platforms (AWS, GCP, Azure) and their AI / ML services.Contributions to open-source projects, publications, or Kaggle competitions.(ref : hirist.tech)