Job Purpose
An experienced AI/ML Engineer to design, develop and maintain AI / ML and GenAI based solutions on enterprise platform on Industry best and open-source models at scale along with governance and security frameworks
Job Responsibilities (JR): 6 8 Areas
Actionable (4-6)
- Design and implement the necessary infrastructure (e.g., compute clusters, storage, networking) for AI applications, including cloud platforms like AWS, Azure, or GCP
- Design, build, and train generative AI models using techniques like deep learning and neural networks
- Develop and maintain scalable, efficient, and reliable data pipelines for AI models, ensuring data quality and integrity.
- Integrate machine learning models into AI platforms and deploy them into production environments, often using AIOps, MLOps and LLMOps frameworks
- Design and implement monitoring strategies for AI platforms and optimize their performance for scalability and real-time applications.
- Perform machine learning tests and statistical analysis to fine-tune the machine learning systems
- Work with the engineering and leadership teams on the functional design, process design, prototyping, testing, performance evaluation and training of AI/ML solutions Extend existing machine learning libraries and frameworks
- Implemented and evaluated machine learning models, including supervised, unsupervised, and reinforcement learning techniques, for B2C use cases
- Strong experience with deep learning frameworks like TensorFlow and PyTorch
- Used Python or other programming models to build and train a deep learning model for Document Classification, Extraction, Signature matching, STT, TTS kind of use cases
- Demonstrated ability to fine-tune and optimize models using large data sets
- Certified in AI/ML in any of the cloud platforms like AWS, Azure, or GCP and experience deploying AI/ML models in the cloud
- Effective communication skills, both written and verbal, with the ability to effectively communicate technical concepts to non-technical audiences
Key Skills :
- Strong background in designing and implementing machine learning and deep learning algorithms and responsible AI practices at enterprise scale and speed
- Working knowledge with ML platforms like TensorFlow, PyTorch, or Hugging Face
- Proficiency in Training, Tuning and Deploying GenAI models based on LLMs, GANs, and VAEs
- Hands on expert in programming languages like Python, Java, or C++, and have experience with cloud platforms, containerization technologies (e.g., Docker, Kubernetes), and data pipeline tools (e.g., Apache Kafka, Spark)
- Experience working in cross-functional teams
- Strong analytical and problem-solving skills
