
Artificial Intelligence/Machine Learning Engineer
2 days ago
Perennial Systems is seeking highly skilled and motivated AI/ML Engineers to join our growing Data & AI team.
This role offers the opportunity to work at the forefront of Generative AI, NLP, and Document AI, collaborating with cross-functional teams to design, develop, and deploy AI-powered solutions that solve real-world business problems.
Responsibilities
Whether you are passionate about building robust, scalable AI systems or conducting research to push the boundaries of machine learning innovation, we offer an environment that fosters autonomy, technical depth, and meaningful Responsibilities :
- Design, build, and deploy scalable AI/ML models and systems for real-world applications.
- Work across Generative AI, NLP, and Document AI to deliver innovative solutions.
- Translate business requirements into technical specifications for AI solutions.
- Explore and experiment with emerging AI models, frameworks, and algorithms.
- Conduct performance benchmarking and fine-tuning of AI/ML models.
- Contribute to internal AI best practices, reusable components, and knowledge sharing.
- Work closely with product managers, data engineers, and software developers to integrate AI capabilities into production systems.
- Ensure models are production-ready, optimized for scalability, and compliant with quality and security standards.
- Monitor model performance post-deployment and implement enhancements.
- Keep up to date with advancements in AI research, tools, and Skills & Qualifications :
- Experience: 3 to 6 years in AI/ML engineering, applied machine learning, or related fields.
- Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Hugging Face, etc.
- Expertise in NLP techniques, large language models (LLMs), and Generative AI frameworks.
- Hands-on experience with data preprocessing, feature engineering, and model evaluation.
- Familiarity with cloud-based AI/ML services (AWS Sagemaker, Azure ML, GCP AI Platform).
- Experience with deploying AI/ML models into production environments.
- Knowledge of MLOps tools and workflows (MLflow, Kubeflow, Docker, Kubernetes).
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
- Ability to work independently in a fast-paced, agile environment.
- Exposure to vector databases, prompt engineering, or retrieval-augmented generation (RAG).
- Contributions to open-source AI projects or published research in relevant fields.
- Experience with document understanding and OCR-based AI solutions
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