NJ Group
2 months ago
Key Responsibilities :
1. Solution Design & Architecture :
- Collaborate with stakeholders to define AI/ML requirements and design end-to-end solutions.
- Architect scalable AI systems that integrate seamlessly with existing platforms and services.
- Ensure implementation of LLM/Generative AI (e.g., ChatGPT, GeminiAI, MetaAI,etc)
- Ensure that AI/ML models and solutions are aligned with business objectives and technical feasibility.
2. Machine Learning Model Development :
- Work with data scientists to implement machine learning algorithms for classification, regression, clustering, and optimization tasks.
- Train, test, and validate AI/ML models to ensure accuracy and reliability.
- Optimize model performance, scalability, and responsiveness for deployment.
3. Data Pipeline Engineering :
- Design and implement data pipelines to feed machine learning models with the required data in real-time or batch processing.
- Ensure data quality, integrity, and security across all stages of the AI/ML solution lifecycle.
4. Integration & Deployment :
- Oversee the integration of AI/ML models into production systems, ensuring smooth deployment and performance.
- Collaborate with DevOps teams to automate and streamline model deployment processes (CI/CD for ML).
5. Monitoring & Maintenance :
- Continuously monitor model performance and accuracy post-deployment.
- Diagnose and resolve any performance issues, ensuring models remain effective over time.
6. Documentation & Reporting:
- Document technical designs, workflows, and processes.
- Report progress to stakeholders and provide recommendations for improvements.
Required Skills & Qualifications :
1. Educational Background:
- Bachelor's/Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
2. Technical Skills :
- Strong understanding of machine learning algorithms (e.g., supervised/unsupervised learning, reinforcement learning).
- Strong understanding and knowledge of LLM , NLP, NLU, Multiple Language Models.
- Proficiency in Python and machine learning libraries like TensorFlow, PyTorch, Scikit-learn, and Keras.
- Experience with data manipulation tools like Pandas, NumPy, and SQL.
- Familiarity with cloud platforms (AWS, Google Cloud, Azure) for AI/ML model deployment.
- Knowledge of DevOps tools for CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes).
- Experience with big data tools such as Apache Spark, Hadoop, etc., is a plus.
3. Problem Solving & Analytical Skills :
- Ability to break down complex problems and deliver AI/ML solutions that are effective and efficient.
- Strong data analysis skills to interpret patterns and insights.
4. Soft Skills :
- Excellent communication and collaboration skills, capable of working across multiple teams.
- Ability to present technical information in a clear, concise manner to non-technical stakeholders.
- Strong attention to detail and organizational skills.
Preferred Qualifications :
- Prior experience in designing and deploying AI/ML solutions in production environments.
- Experience with Natural Language Processing (NLP), Computer Vision, or other AI specializations.
- Familiarity with MLOps practices and tools. (ref:hirist.tech)
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