Architect, Machine Learning

Overview:
**Main Purpose of the Role**:
**Responsibilities**:
**Accountabilities**:

- Lead and manage a team of talented professionals, providing mentorship, guidance, and fostering a culture of innovation and collaboration.
- Drive the development and implementation of innovative machine learning and AI projects, leveraging cutting-edge technologies and industry best practices.
- Collaborate with cross-functional teams, including data scientists, engineers, designers, and product managers, to define project requirements, scope, and objectives.
- Research and evaluate new technologies, frameworks, and tools related to machine learning, generative AI, computer vision, and automation, and make recommendations for their adoption.
- Lead the development and deployment of machine learning models, ensuring their accuracy, reliability, and scalability.
- Drive the implementation of computer vision algorithms and techniques to solve real-world problems and enhance automation processes.
- Explore and experiment with generative AI techniques to generate novel and creative solutions in various domains.
- Collaborate with stakeholders to identify and prioritize areas of innovation, ensuring alignment with business goals and objectives.
- Provide technical leadership and guidance to the team, promoting best practices, knowledge sharing, and continuous learning.
- Manage and track project timelines, budgets, and resources to ensure successful project delivery.

Qualifications:
**Years of Experience**:
1) Degree in Computer Science or Engineering or Equivalent with 6+ years of relevant experience in Computer Science/ Statistical Modelling & Analysis/Operations Research
2) 6+ years of development experience in Python
3) 3+ Years of experience in AI, ML, Deep Learning & Conversational AI Technologies
4) 5+ years of relevant hands-on experience as AI/Automation engineer using any one or more tools Azure ML, Azure AI, Python, Azure Could, SQL, Azure DevOps, Azure Storage and or Databricks
5) 2+ Experience in Architecture and design of cloud-based solutions using Python, R, Conversational AI, ML, Deep Learning technologies.
5) 2+ years of relevant experience on UI Path/OCR tools delivering intelligent automation solutions (preferable)
6) Solid understanding of python libraries for machine learning

**Mandatory Technical Skills**:

- Degree in Computer Science or Engineering or Equivalent with 6+ years of relevant experience in Computer Science/ Statistical Modelling & Analysis/Operations Research / Data Science
- Good understanding of Computer Vision/Image Processing and Deep Learning tools & techniques
- Understands Intelligent Automation solution development methodology and lifecycle
- Conversant with Cloud technologies (preferable MS Azure cloud and Azure DevOps)
- Conversant with OCR technologies (preferable Abby, Microsoft Vision, Google Vision, Tesseract)
- Good knowledge of estimation techniques and proposal writing
- Past working experience on a fast paced and agile environment (SAFe 5)
- Strong architecture & design background and should be able to design and deliver solutions quickly
- Strong analytical thinking, troubleshooting, and ability to manage multiple, concurrent projects
- Exposure to Azure ML and/or Azure data bricks is an added advantage
- Hands-on experience with MS Azure cloud

**Mandatory Non Technical Skills**:

- 1+ year of working experience on tools like Clarity, Azure DevOps, Jira, Git Hub etc.
- 2+ year of working experience on a fast paced and agile environment.
- Previous experience in at least 2-3 Image processing use cases on object detection, tracking, classification, recognition, scene understanding using Keras/Tensorflow/ PyTorch frameworks
- Exposure to DevSecOps process and tools like Azure DevOps.
- Experience working with Business / functional team to identify business problem, assessing the challenges and developing solutions.
- Conversant with Project Planning, Estimation & Analysis process and methodologies

**Differentiating Competencies**:
1) Should be able to work in Matrix environment
2) Build Capabilities by Training people on various Computer Vision, Generative-AI, AI-ML Technology Platforms
3) Drive initiatives from Inception to Delivery
4) should be able to articulate the concepts to various stakeholders to gain the confidence