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Director - Generative AI (17-25 yrs)
Vidpro Consultancy Services
posted 10d ago
Key skills for the job
Company : Altimetrik
Experience : 17 - 25 Years
Location : Bangalore & Chennai
Job Type : Full-Time
Position Overview :
We are seeking an experienced and highly skilled Generative AI Expert to join our team. The ideal candidate will have extensive experience in AI/ML engineering, data engineering, and platform development across multi-cloud hybrid environments. You will be responsible for the architecture, design, and implementation of Generative AI solutions aimed at improving customer experience, personalization, and revenue growth.
Qualifications :
- 17+ years of experience in Software Engineering, 7+ Years into AI/ML, 4+ Years into data engineering, and platform development.
- Master's or equivalent degree in Computer Science, Engineering, or related fields (preferred).
- Certifications in Generative AI, Cloud Computing, and Data Engineering are highly preferred.
- Proven track record of successfully delivering AI/ML industrialization projects, with a focus on real-time and edge AI solutions.
Key Responsibilities :
- Lead Generative AI Initiatives : Lead the development of Generative AI strategies, from ideation to deployment, leveraging advanced AI/ML technologies.
- AI/ML Engineering : Design and implement real-time AI and ML pipelines for feature engineering, model training, and model inferencing.
- GenAI Centre of Excellence (CoE) : Spearhead the establishment and development of GenAI CoE, developing industry-specific archetypes, patterns, and best practices for AI industrialization.
- Platform & Cloud Architecture : Architect and design cloud-native platforms that enable data integration, batch processing, real-time streaming, and model inferencing.
- Model and Data Observability : Champion model performance tracking, model explainability, and self-healing AI systems.
- Data Engineering : Lead efforts to architect and develop complex data pipelines using cutting-edge technologies like in-memory data grids and knowledge graph pipelines.
- Real-time ML & Edge AI : Develop real-time event-driven AI models, including clustering, similarity search, and embedding models for personalized recommendations and customer insights.
- AI/ML Platform Enablement : Drive the deployment of AI/ML platforms-as-a-service, integrating advanced ML tools and frameworks such as TensorFlow, PyTorch, Scikit-learn, and Seldon Core.
- Collaborative Innovation : Collaborate with cross-functional teams and external partners to define and implement cutting-edge AI/ML strategies that drive innovation.
- AI Product Innovation : Lead AI product asset cohorts, including patent filing disclosures, and actively contribute to hackathons, innovation cohorts, and building accelerators for improved business outcomes.
- Cloud Data Engineering & Platform Strategy : Enable cloud and on-prem hybrid solutions for AI model integration and data transformation, working with tools like AWS, Azure, GCP, and Snowflake.
Required Technical Skills :
1. Generative AI Expertise :
- Deep understanding of Generative AI concepts, including transformers, GANs (Generative Adversarial Networks), and autoregressive models.
- Experience in deploying real-time and batch ML models for production-scale applications, leveraging modern ML/DL frameworks.
- Experience in advanced deep learning techniques including Clustering, Similarity Search, Embeddings, and RNN (LSTM).
2. AI/ML Frameworks and Tools :
- Proficiency in TensorFlow, PyTorch, Scikit-learn, Keras, and Hugging Face for building and deploying models.
- Expertise in AI/ML platforms like Domino, Weights & Biases, DataRobot, Comet ML, and Seldon Core for continuous monitoring, evaluation, and deployment of models.
- Knowledge of model interpretability and explainability techniques such as SHAP and LIME.
3. Cloud and Data Platform Expertise :
- Advanced experience in multi-cloud platforms including AWS, Azure, and GCP.
- Experience with Data Lakes, Data Warehouses, Feature Stores, and Data Integration platforms like Talend Cloud, Apache Kafka, and Apache Ignite.
- Expertise in cloud-native architectures, containerization (Kubernetes, Docker), and CI/CD pipelines for AI/ML workflows.
4. Data Engineering & Architecture :
- Proficiency in Big Data technologies such as Hadoop, Spark, and NoSQL databases(MongoDB, Cassandra, Redis, Teradata).
- Experience with streaming data solutions like Apache Kafka, Google Pub/Sub, and real-time data processing tools.
- Knowledge of data modeling, ETL, and data transformation across complex enterprise systems, including legacy systems modernization.
Advanced Programming Skills :
- Strong proficiency in Python, Java, Scala, and experience with Airflow for orchestrating AI/ML pipelines.
- Familiarity with Flask or FastAPI for model inference and API deployment.
AI Democratization & Self-service Enablement :
- Experience in creating self-service platforms for data scientists and business teams to train, deploy, and monitor models using tools like Domino, Comet, or DataRobot.
- Experience in automating and scaling model deployment pipelines, using tools like Docker, Kubernetes, CI/CD systems, and MLflow.
Soft Skills :
- Strong leadership abilities with experience driving AI/ML innovation in large organizations.
- Excellent communication skills for interacting with stakeholders, customers, and internal teams.
- Experience in fostering a culture of innovation, team collaboration, and continuous learning.
Functional Areas: Other
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