Job Title: AI/ML Architect

Experience Level - 7+ years

Job location - Coimbatore (Hybrid)

Job Responsibilities:

Architectural Strategy: Define and implement the AI architecture strategy, ensuring it aligns with business objectives.

Collaboration: Work closely with data scientists, data engineers, developers, and business leaders to identify and pilot AI use cases.

Solution Design: Design scalable, cost-effective AI solutions that meet organizational needs.

Technology Selection: Choose appropriate technologies and tools for AI system development, including cloud, on-premises, or hybrid models.

Implementation: Oversee the implementation of AI systems, ensuring they meet technical and business requirements.

Monitoring and Maintenance: Monitor AI system performance, troubleshoot issues, and ensure regular updates and maintenance.

Auditing: Conduct audits of AI tools and practices, focusing on continuous improvement and ethical AI implementation.

Risk Management: Work with security and risk teams to mitigate risks such as data poisoning and model theft.

Technical Skills

1.       AI and ML Frameworks:

®    Proficiency in frameworks like TensorFlow, PyTorch, Keras, and Scikit-learn.

®    Understanding of various machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.

2.       Programming Languages:

®    Strong coding skills in languages such as Python, R, Java, and C++.

®    Experience with scripting languages like Bash or PowerShell.

3.       Data Management and Analytics:

®    Expertise in data preprocessing, cleaning, and transformation.

®    Knowledge of SQL and NoSQL databases (e.g., MySQL, MongoDB).

®    Familiarity with big data technologies like Hadoop, Spark, and Kafka.

4.       Cloud Platforms:

®    Experience with cloud services such as AWS, Azure, and Google Cloud Platform.

®    Understanding of cloud-based AI services and tools (e.g., AWS Sage Maker, Azure Machine Learning).

5.       DevOps and MLOps:

®    Knowledge of DevOps principles and tools (e.g., Git, Jenkins, Docker, Kubernetes).

®    Experience with MLOps practices for deploying and managing machine learning models in production.

6.       Software Engineering:

®    Strong understanding of software development life cycle (SDLC).

®    Familiarity with version control systems (e.g., Git).

®    Experience with API development and integration.

7.       Data Science and Advanced Analytics:

®    Proficiency in statistical analysis and data visualization tools (e.g., SAS, R, Python libraries like Matplotlib and Seaborn).

®    Knowledge of advanced analytics techniques and tools.

8.       Natural Language Processing (NLP):

®    Experience with NLP techniques and tools (e.g., NLTK, SpaCy, BERT).

®    Understanding of text processing, sentiment analysis, and language modeling.

9.       Computer Vision:

®    Familiarity with computer vision techniques and libraries (e.g., OpenCV, TensorFlow Object Detection API).

®    Experience with image and video processing.

Experience:

• Education: Degree in Computer Science, Engineering, or a related field.
• Experience: Proven track record in AI/ML solution design and implementation, with hands-on experience in developing and deploying AI systems.

Non-Technical Skills:

• Excellent communication and collaboration skills.
• Strong problem-solving and strategic thinking abilities.
• Ability to translate business requirements into technical solutions.
• Continuous learning mindset to stay updated with AI advancements.