Job Description :
Key Responsibilities :
- Build and maintain robust Python applications for AI / ML and automation workflows.
- Deploy, fine-tune, and monitor ML / DL models using frameworks like TensorFlow, PyTorch, Hugging Face.
- Design and manage ETL / data pipelines (batch and real-time) using Apache Spark, Airflow, and Kafka.
- Implement cloud-native deployments on AWS, Azure, or GCP using Docker and Kubernetes.
- Drive and manage MLOps pipelines, including CI / CD for ML, model retraining, and version control using tools like MLflow, Kubeflow.
- Ensure high standards of code quality, testing, and documentation.
- Mentor junior developers and contribute to the growth of the AI / ML engineering team.
Key Requirements :
6- 9 years of overall software development experience with 5+ years in Python for AI / ML applications.Strong hands-on experience with :1. Python frameworks : FastAPI, Django
2. ML / DL frameworks : TensorFlow, PyTorch, Hugging Face Transformers
3. Big data & workflow tools : Apache Spark, Airflow, Kafka
Experience with cloud platforms (AWS, Azure, GCP) and ML services like :1. Amazon SageMaker
2. Azure ML
3. Google Vertex AI
Proficiency in containerization and orchestration tools : Docker, Kubernetes.Solid understanding of MLOps tools : MLflow, Kubeflow, CI / CD pipelines for ML.Preferred (Good to Have) :
Exposure to Generative AI, NLP, or Computer Vision projects.AI / ML / Cloud certifications (AWS, Azure, GCP, TensorFlow, etc.).Experience working in agile environments with cross-functional teams.Educational Qualification :
Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or related fields.
Why Join Us?
Work on global AI / ML & Generative AI projects.Opportunity to shape AI / ML delivery frameworks.Clear path for career growth and leadership roles.Competitive compensation with performance-based Collaborative and innovation-driven work culture.(ref : hirist.tech)