Artificial Intelligence Specialist - Deep/Machine Learning (10-15 yrs)

Job Title: AI Specialist

Location: India (Preferred Bangalore, Chennai, Noida, Hyderabad)

Job Type: Full-time

Mandatory Skills : GenAI Architect

Job Description :

Qualifications:

- PhD or Master's degree in Computer Science, Artificial Intelligence, or a related field.

Experience :

- Around 10 years of professional experience in roles such as Data Scientist or similar positions.

- Proven experience in training large deep learning models and handling real-world data.

- Experience in leading teams and managing complex projects in dynamic environments.

Technical Expertise :

- Strong expertise in Foundation Models and Transformer Models.

- Deep understanding of Machine Learning algorithms, especially their applications to structured data in business contexts.

- Comprehensive knowledge of the challenges and opportunities of applying Generative AI in a business environment.

Preferred Skills :

- Professional experience with Machine Learning on structured data in domains such as ERP or CRM.

- Knowledge of privacy-preserving AI techniques is a plus.

Leadership Skills :

- Exceptional leadership capabilities with a demonstrated history of setting and achieving team goals, delegating responsibilities, and mentoring team members.

- Strong interpersonal and organizational skills to effectively manage and communicate within large, diverse teams.

- Proven ability to deliver results and manage high-stakes projects.

Communication :

- Excellent verbal and written communication skills to articulate complex AI solutions to diverse stakeholders.

Technical Skills :

- Expertise in architecting and deploying generative AI solutions, particularly in large-scale systems.

- Strong experience working with large foundation models like GPT, BERT, T5, etc. , and fine-tuning them for specific applications.

- Deep understanding of Transformer-based architectures, including BERT, GPT, and other variants.

- Hands-on experience with popular frameworks such as TensorFlow, PyTorch, and Keras.

- Expertise in training, fine-tuning, and optimizing large deep learning models using high-performance compute resources (GPUs/TPUs).

- In-depth knowledge of various neural network architectures (CNN, RNN, LSTMs, GANs, etc.

- Proficient in applying both supervised and unsupervised machine learning techniques to diverse data sets.

- Expertise in model evaluation methods, including cross-validation, precision-recall, F1-score, ROC/AUC, etc.

- Knowledge of applying reinforcement learning techniques for real-world problem-solving.

- Familiarity with big data processing frameworks like Apache Spark, Hadoop, or similar platforms for large-scale data manipulation and preprocessing.

- Skilled in handling noisy, missing, and unstructured data, and transforming it for AI model use.

- Experience with distributed computing models for training large-scale machine learning models