About the Role :
We are seeking a highly skilled AI / ML Engineer with hands-on expertise in Generative AI, Deep Learning, LLMs, NLP, and modern cloud technologies. The ideal candidate will have a proven track record of transforming POCs into production-grade AI solutions and driving impactful business outcomes.
Key Responsibilities :
- Design, develop, and deploy advanced AI / ML solutions, with a focus on GenAI, Deep Learning, LLMs, and NLP.
- Build, train, and optimize ML models using TensorFlow, PyTorch, or other leading frameworks.
- Develop data pipelines and workflows for preprocessing, feature engineering, and model evaluation.
- Work closely with cross-functional teams to translate business problems into AI-driven solutions.
- Manage end-to-end model lifecycle from experimentation to deployment and monitoring in production.
- Leverage cloud platforms (AWS / Azure / GCP) for scalable AI development, including tools like EC2, ASG, S3, and RDS.
- Implement best practices for version control, code review, and model governance.
- Create clear technical documentation and communicate results to technical and non-technical stakeholders.
Requirements / Qualifications :
3+ years of relevant experience in AI / ML development.Programming : Proficiency in Python, Java, or similar. AI / ML Expertise : Strong hands-on experience with GenAI, Deep Learning, LLMs, and NLP.Frameworks : TensorFlow, PyTorch, scikit-learn.Data Handling : Pandas, NumPy for data manipulation; Matplotlib, Seaborn for visualization.Cloud Platforms : Experience with AWS, Azure, or Google Cloud.Databases : Proficiency in SQL / NoSQL systems.Version Control : Git.Demonstrated success in transforming at least 3 POCs into production-grade solutions.Strong portfolio showcasing end-to-end AI / ML deployments.Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.Excellent problem-solving abilities with a collaborative, agile mindset.Strong communication skills to work effectively across teams.Nice to Have :
Advanced knowledge of cloud tools such as EC2, ASG, S3, RDS for scalable AI development.Exposure to MLOps practices and CI / CD pipelines for model deployment.Experience with containerization (Docker, Kubernetes).(ref : hirist.tech)